Columbia University
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Showing 117 courses from Columbia
Artificial Intelligence - Columbia University
Columbia University (via edX)
Artificial Intelligence - Columbia University is a comprehensive intermediate-level resource offered by Columbia University, focused on building practical skills in artificial intelligence and machine learning. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in artificial intelligence and machine learning, including machine learning algorithms, deep learning, NLP, computer vision, and model deployment. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 60 hours of content, designed to be completed in 6-12 weeks at a comfortable pace. Basic familiarity with the subject area is recommended. You should have completed a beginner-level course or have equivalent self-taught knowledge. Comfort with using a computer and basic problem-solving skills will help. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into artificial intelligence and machine learning Freelancers wanting to add new services to their portfolio Self-learners passionate about artificial intelligence and machine learning and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as ML Engineer, AI Engineer, Data Scientist, Research Scientist. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 8-15 LPA Mid-level / 2-5 years: Rs 18-35 LPA Senior / 5+ years: Rs 40-80 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Microsoft, OpenAI, Indian AI startups, research labs. India is the second-largest AI talent pool globally, and the demand far exceeds supply. The Indian AI market is expected to reach $17 billion by 2027. Every major Indian tech company — from Infosys to Reliance to Jio — is investing heavily in AI capabilities. The emergence of generative AI has created entirely new job categories that didn't exist two years ago. ML engineers with LLM experience are commanding Rs 30-60 LPA even at early career stages. Columbia University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Machine Learning - Columbia University
Columbia University (via edX)
Machine Learning - Columbia University is a comprehensive advanced-level resource offered by Columbia University, focused on building practical skills in data science and analytics. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in data science and analytics, including Python, SQL, Pandas, NumPy, data visualization, statistics, and machine learning basics. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Build supervised and unsupervised ML models with scikit-learn Master regression, classification, and clustering algorithms Evaluate models using cross-validation and proper metrics Deploy ML models to production Duration: Estimated duration: 40 hours of content, designed to be completed in 4-8 weeks at a comfortable pace. This is an advanced resource meant for learners who already have solid fundamentals. You should have at least 6 months of hands-on experience or have completed intermediate-level courses in this area. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into data science and analytics Freelancers wanting to add new services to their portfolio Self-learners passionate about data science and analytics and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Data Analyst, Business Analyst, Data Scientist, Analytics Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-8 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include TCS, Infosys, Flipkart, Amazon, Swiggy, Zomato, PhonePe. The data science industry in India is projected to grow at 27% CAGR through 2028. Companies across all sectors — from banking (HDFC, ICICI) to e-commerce (Flipkart, Amazon) to healthcare (Practo, PharmEasy) — are building data teams. India currently has a shortage of 200,000+ data professionals, making this one of the best fields to enter right now. Cities like Bangalore, Hyderabad, Pune, and Gurgaon have the highest concentration of data science jobs. Columbia University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Corporate Entrepreneurship
Columbia University (via edX)
Corporate Entrepreneurship
Corporate Entrepreneurship: Accelerating Organizational Innovation
Columbia University (via edX)
Corporate Entrepreneurship: Accelerating Organizational Innovation
Introduction to Corporate Finance
Columbia University (via edX)
Introduction to Corporate Finance
Corporate Finance: Part I, Introduction and Tools
Columbia University (via edX)
Corporate Finance: Part I, Introduction and Tools
Free Cash Flow Analysis
Columbia University (via edX)
Free Cash Flow Analysis
The Free Cash Flow Method for Firm Valuation
Columbia University (via edX)
The Free Cash Flow Method for Firm Valuation
Risk & Return
Columbia University (via edX)
Risk & Return
Risk and Return and the Weighted Average Cost of Capital
Columbia University (via edX)
Risk and Return and the Weighted Average Cost of Capital
INSPIRE
Columbia University (via edX)
INSPIRE
Crisis Resource Management
Columbia University (via edX)
Crisis Resource Management
Construction Scheduling
Columbia University (via Coursera)
This course focuses on learning how to develop and manage a schedule. The first module provides an overview of the Construction Scheduling course. The second module introduces bar or Gantt charts and how they are used as scheduling tools. During the third module, learners will create activity precedence diagrams, also referred to as activity on node diagrams, which graphically represent the construction activities in a project and their relationships. The fourth module provides an overview of the types of construction activity relationships encountered in a construction project and how to represent them in an activity precedence diagram. Forward and backward pass calculations are covered in the fifth module, and during the sixth module, Professor Odeh discusses the importance of critical paths, including what it is and why it is important. By the end of this course, you will be able to: -Discover key project scheduling techniques and procedures -Learn how to develop and manage a schedule, and understand scheduling tools such as bar charts, activity on arrow, and activity on nodes -Explore the multiple relationships that connect all the construction activities in our project from start to finish -Learn about creating a network diagram, defining the importance of the critical path in a project network, and defining project activities float -Understand the fundamentals of bar charts, precedence diagrams, activity on arrow, Program -Evaluation and Review Technique (PERT), range estimating, linear project operations, and the line of balance (LOB)
Artificial Intelligence (AI)
Columbia University (via edX)
Artificial Intelligence (AI)
Machine Learning
Columbia University (via edX)
Machine Learning
Robotics
Columbia University (via edX)
Robotics
The Age of Sustainable Development
Columbia University (via Coursera)
The Age of Sustainable Development" gives students an understanding of the key challenges and pathways to sustainable development - that is, economic development that is also socially inclusive and environmentally sustainable.
Animation and CGI Motion
Columbia University (via edX)
Animation and CGI Motion
[Dev Sandbox] Introduction to Social Science Experiments
Columbia University (via edX)
[Dev Sandbox] Introduction to Social Science Experiments
Advanced Topics in Derivative Pricing
Columbia University (via Coursera)
This course discusses topics in derivative pricing. The first module is designed to understand the Black-Scholes model and utilize it to derive Greeks, which measures the sensitivity of option value to variables such as underlying asset price, volatility, and time to maturity. Greeks are important in risk management and hedging and often used to measure portfolio value change. Then we will analyze risk management of derivatives portfolios from two perspectives—Greeks approach and scenario analysis. The second module reveals how option’s theoretical price links to real market price—by implied volatility. We will discuss pricing by volatility surface as well as explanations of volatility smile and skew, which are common in real markets. The third module involves topics in credit derivatives and structured products and focuses on Credit Debit Obligation (CDO), which played an important part in the past financial crisis starting from 2007. We will cover CDO’s definition, simple and synthetic versions of CDO, and CDO portfolios. The final module is the application of option pricing methodologies and takes natural gas and electricity related options as an example to introduce valuation methods such as dynamic programming in real options.
Essential Math for AI
Columbia University (via edX)
Essential Math for AI
Programming & Data Structures
Columbia University (via edX)
Programming & Data Structures
Statistical Thinking for Data Science and Analytics
Columbia University (via edX)
Statistical Thinking for Data Science and Analytics
Machine Learning for Data Science and Analytics
Columbia University (via edX)
Machine Learning for Data Science and Analytics
Enabling Technologies for Data Science and Analytics: The Internet of Things
Columbia University (via edX)
Enabling Technologies for Data Science and Analytics: The Internet of Things
Freedom of Expression in the Age of Globalization
Columbia University (via edX)
Freedom of Expression in the Age of Globalization
CTL Course - Sandbox
Columbia University (via edX)
CTL Course - Sandbox
Intro to Social Science Experiments Sandbox
Columbia University (via edX)
Intro to Social Science Experiments Sandbox
Frontiers of Science: Climate & Us
Columbia University (via edX)
Frontiers of Science: Climate & Us
Camera and Imaging
Columbia University (via edX)
Camera and Imaging
Features and Boundaries
Columbia University (via edX)
Features and Boundaries
3D Reconstruction - Single Viewpoint
Columbia University (via edX)
3D Reconstruction - Single Viewpoint
3D Reconstruction - Multiple Viewpoints
Columbia University (via edX)
3D Reconstruction - Multiple Viewpoints
Visual Perception
Columbia University (via edX)
Visual Perception
Find Your Calling: Career Transition Principles for Returning Veterans
Columbia University (via edX)
Find Your Calling: Career Transition Principles for Returning Veterans
Decision Making and Reinforcement Learning
Columbia University (via Coursera)
This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods. Finally, we introduce the reinforcement learning problem and discuss two paradigms: Monte Carlo methods and temporal difference learning. We conclude the course by noting how the two paradigms lie on a spectrum of n-step temporal difference methods. An emphasis on algorithms and examples will be a key part of this course.
Freedom of Expression and Information in the Time of Globalization: Foundational Course
Columbia University (via edX)
Freedom of Expression and Information in the Time of Globalization: Foundational Course
Global Freedom of Expression and Information in the Time of Globalization: Foundational Course
Columbia University (via edX)
Global Freedom of Expression and Information in the Time of Globalization: Foundational Course
Construction Cost Estimating and Cost Control
Columbia University (via Coursera)
This course introduces the types of cost estimation from the conceptual design phase through the more detailed design phase of a construction project. In addition, the course highlights the importance of controlling costs and how to monitor project cash flow. Learners will work on a break-even analysis of construction tasks in a project. The course begins with Professor Odeh providing an overview of what will be covered. Next, learners explore the stages of design in a construction project. Professor Odeh then describes the types of cost estimates in a construction project, and the tools and methods used to create estimates. By the end of this course, you will be able to: -Acquire the fundamentals of cost estimation and the design phase to perform cost estimation -Learn about cost control and cost control methods, emphasizing the Earned Value Method or EVM -Understand the close out period of the project by exploring the punch lists, final approval, and turnover to the client
Freedom of Expression and Information in the Time of Globalization: Advanced Course
Columbia University (via edX)
Freedom of Expression and Information in the Time of Globalization: Advanced Course
Global Muckraking: Investigative Journalism and Global Media
Columbia University (via edX)
Global Muckraking: Investigative Journalism and Global Media
The Civil War and Reconstruction - 1850-1861: A House Divided
Columbia University (via edX)
The Civil War and Reconstruction - 1850-1861: A House Divided
The Civil War and Reconstruction - 1850-1861
Columbia University (via edX)
The Civil War and Reconstruction - 1850-1861
The Civil War and Reconstruction - 1861 - 1865: A New Birth of Freedom
Columbia University (via edX)
The Civil War and Reconstruction - 1861 - 1865: A New Birth of Freedom
The Civil War and Reconstruction - 1861-1865
Columbia University (via edX)
The Civil War and Reconstruction - 1861-1865
The Civil War and Reconstruction - 1865-1890
Columbia University (via edX)
The Civil War and Reconstruction - 1865-1890
The Civil War and Reconstruction – 1865-1890: The Unfinished Revolution
Columbia University (via edX)
The Civil War and Reconstruction – 1865-1890: The Unfinished Revolution
Columbia HLS Video workflow Course
Columbia University (via edX)
Columbia HLS Video workflow Course
Inclusive Teaching: Supporting All Students in the College Classroom
Columbia University (via edX)
Inclusive Teaching: Supporting All Students in the College Classroom
Innovating Instruction: Reimagining Teaching with Technology
Columbia University (via edX)
Innovating Instruction: Reimagining Teaching with Technology
Indigenous Peoples' Rights
Columbia University (via edX)
Indigenous Peoples' Rights
Columbia Engineering Machine Learning & AI MicroBootCamp
Columbia University (via edX)
Columbia Engineering Machine Learning & AI MicroBootCamp
Menstruation in a Global Context: Addressing Policy and Practice
Columbia University (via edX)
Menstruation in a Global Context: Addressing Policy and Practice
Beyond Zoom: Blended Online Learning
Columbia University (via edX)
Beyond Zoom: Blended Online Learning
Protecting Children in Humanitarian Settings
Columbia University (via edX)
Protecting Children in Humanitarian Settings
Public Health Advocacy Academy
Columbia University (via edX)
Public Health Advocacy Academy
Soins infirmiers en VIH pédiatrique
Columbia University (via edX)
Soins infirmiers en VIH pédiatrique
Pediatric HIV
Columbia University (via edX)
Pediatric HIV
Public Sector Innovation Lab
Columbia University (via edX)
Public Sector Innovation Lab
Blended Learning Toolkit
Columbia University (via edX)
Blended Learning Toolkit
Digital Case Method
Columbia University (via edX)
Digital Case Method
Learning Success
Columbia University (via edX)
Learning Success
Supporting Veteran Success in Higher Education
Columbia University (via edX)
Supporting Veteran Success in Higher Education
University Studies for Student Veterans
Columbia University (via edX)
University Studies for Student Veterans
HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Clinical Perspective)
Columbia University (via Coursera)
HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is a 12-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. Also, it has additional, optional modules on other topics of interest or relevance. Although we suggest to complete the course within a month's timeframe, the course is self-paced and so you can start and finish the course at anytime during a month's time period. No additional hardware or software are required for this course. Our nation’s healthcare system is changing at a rapid pace. Transformative health care delivery programs depend heavily on health information technology to improve and coordinate care, maintain patient registries, support patient engagement, develop and sustain data infrastructure necessary for multi-payer value-based payment, and enable analytical capacities to inform decision making and streamline reporting. The accelerated pace of change from new and expanding technology will continue to be a challenge for preparing a skilled workforce so taking this training will help you to stay current in the dynamic landscape of health care. This course is one of three related courses in the HI-FIVE training program, which has topics on population health, care coordination and interoperability, value-based care, healthcare data analytics, and patient-centered care. Each of the three courses is designed from a different perspective based on various healthcare roles. This first course is from a clinical perspective, geared towards physicians, nurse practitioners, physician assistants, nurses, clinical executives and managers, medical assistants, and other clinical support roles. However, we encourage anyone working in healthcare, health IT, public health, and population health to participate in any of the three trainings.
Women Have Always Worked: The U.S. Experience 1700 - 1920
Columbia University (via edX)
Women Have Always Worked: The U.S. Experience 1700 - 1920
Women Have Always Worked: The U.S. Experience 1920 - 2016
Columbia University (via edX)
Women Have Always Worked: The U.S. Experience 1920 - 2016
Seeking Women’s Rights: Colonial Period to the Civil War
Columbia University (via edX)
Seeking Women’s Rights: Colonial Period to the Civil War
Wage Work for Women Citizens: 1870-1920
Columbia University (via edX)
Wage Work for Women Citizens: 1870-1920
Negotiating a Changing World: 1920-1950
Columbia University (via edX)
Negotiating a Changing World: 1920-1950
Fighting for Equality: 1950–2018
Columbia University (via edX)
Fighting for Equality: 1950–2018
Causal Inference 2
Columbia University (via Coursera)
This course offers a rigorous mathematical survey of advanced topics in causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships. We will study advanced topics in causal inference, including mediation, principal stratification, longitudinal causal inference, regression discontinuity, interference, and fixed effects models.
Economics of Money and Banking
Columbia University (via Coursera)
The last three or four decades have seen a remarkable evolution in the institutions that comprise the modern monetary system. The financial crisis of 2007-2009 is a wakeup call that we need a similar evolution in the analytical apparatus and theories that we use to understand that system. Produced and sponsored by the Institute for New Economic Thinking, this course is an attempt to begin the process of new economic thinking by reviving and updating some forgotten traditions in monetary thought that have become newly relevant. Three features of the new system are central. Most important, the intertwining of previously separate capital markets and money markets has produced a system with new dynamics as well as new vulnerabilities. The financial crisis revealed those vulnerabilities for all to see. The result was two years of desperate innovation by central banking authorities as they tried first this, and then that, in an effort to stem the collapse. Second, the global character of the crisis has revealed the global character of the system, which is something new in postwar history but not at all new from a longer time perspective. Central bank cooperation was key to stemming the collapse, and the details of that cooperation hint at the outlines of an emerging new international monetary order. Third, absolutely central to the crisis was the operation of key derivative contracts, most importantly credit default swaps and foreign exchange swaps. Modern money cannot be understood separately from modern finance, nor can modern monetary theory be constructed separately from modern financial theory. That's the reason this course places dealers, in both capital markets and money markets, at the very center of the picture, as profit-seeking suppliers of market liquidity to the new system of market-based credit.
Features and Boundaries
Columbia University (via Coursera)
This course focuses on the detection of features and boundaries in images. Feature and boundary detection is a critical preprocessing step for a variety of vision tasks including object detection, object recognition and metrology – the measurement of the physical dimensions and other properties of objects. The course presents a variety of methods for detecting features and boundaries and shows how features extracted from an image can be used to solve important vision tasks. We begin with the detection of simple but important features such as edges and corners. We show that such features can be reliably detected using operators that are based on the first and second derivatives of images. Next, we explore the concept of an “interest point” – a unique and hence useful local appearance in an image. We describe how interest points can be robustly detected using the SIFT detector. Using this detector, we describe an end-to-end solution to the problem of stitching overlapping images of a scene to obtain a wide-angle panorama. Finally, we describe the important problem of finding faces in images and show several applications of face detection.
Digital Case Method
Columbia University (via Coursera)
The course is suited for teaching and learning professionals, media professors, university leaders, and educators interested in learning, creating, and using Digital Case Studies. This course will allow learners to tap into the power of visual storytelling through the powerful format of the digital case study, which can and should be created by students themselves. This class uses video tutorials and practical guides to teach learners case creation using inexpensive tools such as a smartphone, stabilizer, and Adobe Premiere Software. It also dives into how to design, fund, and manage education programs built on digital case studies. To be successful in this course no pre-requisite filmmaking knowledge is required. An interest in documentary-style filmmaking and video editing is all you need.
Supporting Veteran Success in Higher Education
Columbia University (via Coursera)
This course is designed to be a training that familiarizes any faculty or staff member at a college or university with military and veteran culture as well as veteran-specific considerations in the areas of admissions, finances, academic and student life, and health and well-being. Our hope is that the information provided here will deepen the understanding of student veterans, resulting in a more veteran inclusive campus.
Find Your Calling: Career Transition Principles for Veterans
Columbia University (via Coursera)
This course provides military veterans with a useful roadmap to transition more smoothly from military service to a new and meaningful civilian career.
HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective)
Columbia University (via Coursera)
HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is an approximately 10-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. No additional hardware or software are required for this course. Our nation’s healthcare system is changing at a rapid pace. Transformative health care delivery programs depend heavily on health information technology to improve and coordinate care, maintain patient registries, support patient engagement, develop and sustain data infrastructure necessary for multi-payer value-based payment, and enable analytical capacities to inform decision making and streamline reporting. The accelerated pace of change from new and expanding technology will continue to be a challenge for preparing a skilled workforce so taking this training will help you to stay current in the dynamic landscape of health care. This course is one of three related courses in the HI-FIVE training program, which has topics on population health, care coordination and interoperability, value-based care, healthcare data analytics, and patient-centered care. Each of the three courses is designed from a different perspective based on various healthcare roles. This third course is from an administrative or IT perspective, geared towards executives, managers, analysts, and staff that work in administration, business, finance, operations, data or IT. However, we encourage anyone working in healthcare, health IT, public health, and population health to participate in any of the three trainings.
The Construction Industry: The Way Forward
Columbia University (via Coursera)
This final course in the specialization provides an introduction on types of the construction projects as well as the main concern of the productivity challenge in the construction industry. Through case studies, you will learn the industry characteristics and its unique environment that led to such productivity performance as well as touch base on other several examples of challenges we are facing internally in the industry. In the 2nd part of the course, Professor Odeh will give an overview of 10 mega trends that are making us change the way we think about construction. Furthermore, Professor Odeh will discuss the main role of three levels on what needs to be done: an industry collaborative effort and role; a government role; and last but not least a company role. In this discussion, Professor Odeh will also touch base on several technological and innovative trends that are rising in our construction industry. By the end of this course, you will be able to: -Understand the overall history of construction industry -Analyze the optimal ways to respond to the opportunities and challenges brought by current industrial trends such as aging infrastructure, climate change, sustainability trends and tools, the rise of urbanization, and an aging/shrinking workforce -Recognize the importance of collaborating with governments and public officials in pursuit of industry transformation -Comprehend the rising technological trends in the AEC industry and give examples of how to apply technology to the construction industry
Introduction to Financial Engineering and Risk Management
Columbia University (via Coursera)
Introduction to Financial Engineering and Risk Management course belongs to the Financial Engineering and Risk Management Specialization and it provides a fundamental introduction to fixed income securities, derivatives and the respective pricing models. The first module gives an overview of the prerequisite concepts and rules in probability and optimization. This will prepare learners with the mathematical fundamentals for the course. The second module includes concepts around fixed income securities and their derivative instruments. We will introduce present value (PV) computation on fixed income securities in an arbitrage free setting, followed by a brief discussion on term structure of interest rates. In the third module, learners will engage with swaps and options, and price them using the 1-period Binomial Model. The final module focuses on option pricing in a multi-period setting, using the Binomial and the Black-Scholes Models. Subsequently, the multi-period Binomial Model will be illustrated using American Options, Futures, Forwards and assets with dividends.
Optimization Methods in Asset Management
Columbia University (via Coursera)
This course focuses on applications of optimization methods in portfolio construction and risk management. The first module discusses portfolio construction via Mean-Variance Analysis and Capital Asset Pricing Model (CAPM) in an arbitrage-free setting. Next, it demonstrates the application of the security market line and sharpe optimal portfolio in the exercises. The second module involves the difficulties in implementing Mean-Variance techniques in a real-world setting and the potential methods to deal with it. We will introduce Value at Risk (VaR) and Conditional Value at Risk (CVaR) as risk measurements, and Exchange Traded Funds (ETFs), which play an important role in trading and asset management. Typical statistical biases, pitfalls, and their underlying reasons are also discussed, in order to achieve better results when completing real statistical estimation. The final module looks directly at real-world transaction costs modeling. It includes the basic market micro-structures including order book, bid-ask spread, measurement of liquidity, and their effects on transaction costs. Then we enrich Mean-Variance portfolio strategies by considering transaction costs.
Camera and Imaging
Columbia University (via Coursera)
This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or processing by a human or a machine. Imaging has a long history, spanning several centuries. But the advances made in the last three decades have revolutionized the camera and dramatically improved the robustness and accuracy of computer vision systems. We describe the fundamentals of imaging, as well as recent innovations in imaging that have had a profound impact on computer vision. This course starts with examining how an image is formed using a lens camera. We explore the optical characteristics of a camera such as its magnification, F-number, depth of field and field of view. Next, we describe how solid-state image sensors (CCD and CMOS) record images, and the key properties of an image sensor such as its resolution, noise characteristics and dynamic range. We describe how image sensors can be used to sense color as well as capture images with high dynamic range. In certain structured environments, an image can be thresholded to produce a binary image from which various geometric properties of objects can be computed and used for recognizing and locating objects. Finally, we present the fundamentals of image processing – the development of computational tools to process a captured image to make it cleaner (denoising, deblurring, etc.) and easier for computer vision systems to analyze (linear and non-linear image filtering methods).
Attaining Higher Education
Columbia University (via Coursera)
Prepare to transition to college using intentional decision-making. Aimed at active duty service members and veterans, with this course you will learn about the college admission process, including financial aid, to help you choose a right-fit college.
University Studies for Student Veterans
Columbia University (via Coursera)
The skills you learned in the military will go a long way toward helping you succeed in college, but if you’re looking for some extra support – or an academic tune-up – then you’ll find it in this course. We know that the culture of higher education is different from the culture of the military in meaningful ways, and we also know that one of the keys to excelling in college–especially for student veterans–is learning to navigate these differences successfully, right from the very start. This course aims to help you do just that. First, the course will orient you to the norms and expectations of the college classroom. The quicker you know what is expected of you, the quicker you can start learning. Second, the course will offer you strategies to ease your transition, to help you achieve your academic goals, and to allow you to make the most of your college education. While this course is open to everyone, the content has been tailored specifically for student veterans currently pursuing higher education, active duty service members who aspire to start school or return to school soon, and higher education professionals who work to support student veterans at their schools. If this sounds like you, and if you’re ready to learn how to make your transition easier and more successful, then we hope you’ll join us. This online curriculum may be used in a variety of ways, including, but not limited to, as a start-to finish, self-directed online experience (MOOC). It can also, in its current format, serve as an “orientation” for other student veteran success programs. We also invite you to utilize this resource as a library/toolkit of academic success strategies, a tool for flipped classroom pedagogy, or a companion text for on-the-ground transition courses. We welcome the opportunity to assist higher education institutions (both 2-year and 4-year), military installation education services officers and transition assistance programs, veteran focused non-profit organizati...
3D Reconstruction - Multiple Viewpoints
Columbia University (via Coursera)
This course focuses on the recovery of the 3D structure of a scene from images taken from different viewpoints. We start by first building a comprehensive geometric model of a camera and then develop a method for finding (calibrating) the internal and external parameters of the camera model. Then, we show how two such calibrated cameras, whose relative positions and orientations are known, can be used to recover the 3D structure of the scene. This is what we refer to as simple binocular stereo. Next, we tackle the problem of uncalibrated stereo where the relative positions and orientations of the two cameras are unknown. Interestingly, just from the two images taken by the cameras, we can both determine the relative positions and orientations of the cameras and then use this information to estimate the 3D structure of the scene. Next, we focus on the problem of dynamic scenes. Given two images of a scene that includes moving objects, we show how the motion of each point in the image can be computed. This apparent motion of points in the image is called optical flow. Optical flow estimation allows us to track scene points over a video sequence. Next, we consider the video of a scene shot using a moving camera, where the motion of the camera is unknown. We present structure from motion that takes as input tracked features in such a video and determines not only the 3D structure of the scene but also how the camera moves with respect to the scene. The methods we develop in the course are widely used in object modeling, 3D site modeling, robotics, autonomous navigation, virtual reality and augmented reality.
HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Social/Peer Perspective)
Columbia University (via Coursera)
HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is an approximately 10-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. No additional hardware or software are required for this course. Our nation’s healthcare system is changing at a rapid pace. Transformative health care delivery programs depend heavily on health information technology to improve and coordinate care, maintain patient registries, support patient engagement, develop and sustain data infrastructure necessary for multi-payer value-based payment, and enable analytical capacities to inform decision making and streamline reporting. The accelerated pace of change from new and expanding technology will continue to be a challenge for preparing a skilled workforce so taking this training will help you to stay current in the dynamic landscape of health care. This course is one of three related courses in the HI-FIVE training program, which has topics on population health, care coordination and interoperability, value-based care, healthcare data analytics, and patient-centered care. Each of the three courses is designed from a different perspective based on various healthcare roles. This second course is from a social or peer perspective, geared towards care coordinators, care/case managers, social workers, community health workers, patient navigators, peer coaches, behavioral health support, and other similar roles. However, we encourage anyone working in healthcare, health IT, public health, and population health to participate in any of the three trainings.
Causal Inference
Columbia University (via Coursera)
This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships. We will study methods for collecting data to estimate causal relationships. Students will learn how to distinguish between relationships that are causal and non-causal; this is not always obvious. We shall then study and evaluate the various methods students can use — such as matching, sub-classification on the propensity score, inverse probability of treatment weighting, and machine learning — to estimate a variety of effects — such as the average treatment effect and the effect of treatment on the treated. At the end, we discuss methods for evaluating some of the assumptions we have made, and we offer a look forward to the extensions we take up in the sequel to this course.
Visual Perception
Columbia University (via Coursera)
The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The first is the separation of an image into object and background using a technique called change detection. The second is the tracking of one or more objects in a video. Next, we examine the problem of segmenting an image into meaningful regions. In particular, we take a bottom-up approach where pixels with similar attributes are grouped together to obtain a region. Finally, we tackle the problem of object recognition. We describe two approaches to the problem. The first directly recognize an object and its pose using the appearance of the object. This method is based on the concept of dimension reduction, which is achieved using principal component analysis. The second approach is to use a neural network to solve the recognition problem as one of learning a mapping from the input (image) to the output (object class, object identity, activity, etc.). We describe how a neural network is constructed and how it is trained using the backpropagation algorithm.
Term-Structure and Credit Derivatives
Columbia University (via Coursera)
This course will focus on capturing the evolution of interest rates and providing deep insight into credit derivatives. In the first module we discuss the term structure lattice models and cash account, and then analyze fixed income derivatives, such as Options, Futures, Caplets and Floorlets, Swaps and Swaptions. In the second module, we will examine model calibration in the context of fixed income securities and extend it to other asset classes and instruments. Learners will operate model calibration using Excel and apply it to price a payer swaption in a Black-Derman-Toy (BDT) model. The third module introduces credit derivatives and subsequently focuses on modeling and pricing the Credit Default Swaps. In the fourth module, learners would be introduced to the concept of securitization, specifically asset backed securities(ABS). The discussion progresses to Mortgage Backed Securities(MBS) and the associated mortgage mathematics. The final module delves into introducing and pricing Collateralized Mortgage Obligations(CMOs).
Computational Methods in Pricing and Model Calibration
Columbia University (via Coursera)
This course focuses on computational methods in option and interest rate, product’s pricing and model calibration. The first module will introduce different types of options in the market, followed by an in-depth discussion into numerical techniques helpful in pricing them, e.g. Fourier Transform (FT) and Fast Fourier Transform (FFT) methods. We will explain models like Black-Merton-Scholes (BMS), Heston, Variance Gamma (VG), which are central to understanding stock price evolution, through case studies and Python codes. The second module introduces concepts like bid-ask prices, implied volatility, and option surfaces, followed by a demonstration of model calibration for fitting market option prices using optimization routines like brute-force search, Nelder-Mead algorithm, and BFGS algorithm. The third module introduces interest rates and the financial products built around these instruments. We will bring in fundamental concepts like forward rates, spot rates, swap rates, and the term structure of interest rates, extending it further for creating, calibrating, and analyzing LIBOR and swap curves. We will also demonstrate the pricing of bonds, swaps, and other interest rate products through Python codes. The final module focuses on real-world model calibration techniques used by practitioners to estimate interest rate processes and derive prices of different financial products. We will illustrate several regression techniques used for interest rate model calibration and end the module by covering the Vasicek and CIR model for pricing fixed income instruments.
Pets, Politics and Pandemics
Columbia University (via Coursera)
This course is designed to be a fun and accessible introduction to the topic of systems theory. Systems theory describes a number of fundamental concepts that undergird a broad array of phenomena across many different social, political and natural arenas. It is from this broad applicability that the course derives its title: Pets (social), politics (political and economic) and Pandemics (natural). Despite being, hopefully, fun, the course has a serious intent as it aims to teach enough systems theoretical methods so that after taking the course the student can apply it to their own life to gain new insights into things they may have been studying already for a while. The material within this course can be applied across broad contexts, such as making difficult choices and communicating your ideas effectively to peers. After all, there are indeed strategies for navigating situations in life with the help of lessons from science. In the course, with the help of Professor Billinge's dogs, we will grapple with social justice, climate change, propaganda and disinformation, the origin of the unidirectionality of time and watch some relaxing views of birds flying around with nice music playing.
Become a Peer Sponsor: Intro to Military Transition Support
Columbia University (via Coursera)
The Department of Veterans Affairs’ Veteran Sponsorship Initiative (VSI) provides manualized, certification training to individuals interested in supporting service members and veterans as they transition from military service. The VSI is an evidence-based program designed to reduce transition stressors by matching service members with a community-based sponsor who helps them rejoin their civilian communities by assisting with housing, employment, educational opportunities, and access to mental health support. Participating in this course will equip you with the foundational skills needed to best support military service members and veterans in their transition journey.
Construction Finance
Columbia University (via Coursera)
This course expands the knowledge of a construction project manager to include an understanding of economics and the mathematics of money, an essential component of every construction project. Topics covered include the time value of money, the definition and calculation of the types of interest rates, and the importance of Cash Flow Diagrams. The course covers these topics in three sections. The first section focuses on the foundation of building the mathematics of money, often referred to as value of money. It also highlights the present value techniques and the internal rate of return from a construction manager point of view. The second section of the course focuses on vertical construction finance and the last part focuses on horizontal construction finance. Under the vertical construction finance, the instructor discusses real estate finance and how that has been done with more in-depth details and gives examples for students to solve with instructions. The last topic, horizontal finance, is divided into two parts. To begin, the instructor introduces vast details about public private partnership. This module highlights around three case studies about PPP projects, which would be an introduction to project financing in horizontal work. After introducing case studies, the instructor demonstrates the risks associated with construction finance. After that, similar to the previous three courses, the course finishes with emphasizing the importance of construction finance.
Construction Project Management
Columbia University (via Coursera)
Construction Project Management introduces learners to Project Initiation and Planning. Columbia University professor, Ibrahim Odeh, along with industry experts join together to provide a comprehensive overview of the construction industry. There are 10 modules that allow learners to become knowledgeable of construction management within the dynamic construction industry. Professor Odeh teaches learners about the fundamentals of the Project Development Cycle while guest lecturers discuss Lean Project Delivery method and Lean Design Behaviors. Technological advances, such as Building Information Modeling (BIM), will be introduced with real world examples of the uses of BIM during the Lifecycle of the Project. The course concludes with Professor Odeh discussing the importance of project planning and scheduling and an opportunity to develop a Work Breakdown Structure. By the end of this course, you will be able to: -Learn about construction management, including an understanding of the construction industry, the role of a project manager, construction contract types, and project delivery methods -Explain the fundamental principles to establish Environment, Health and Safety in the construction industry -Detail the principles and application of sustainability development in construction industry -Summarize the work breakdown structure (WBS) and estimate the construction activity duration
3D Reconstruction - Single Viewpoint
Columbia University (via Coursera)
This course focuses on the recovery of the 3D structure of a scene from its 2D images. In particular, we are interested in the 3D reconstruction of a rigid scene from images taken by a stationary camera (same viewpoint). This problem is interesting as we want the multiple images of the scene to capture complementary information despite the fact that the scene is rigid and the camera is fixed. To this end, we explore several ways of capturing images where each image provides additional information about the scene. In order to estimate scene properties (depth, surface orientation, material properties, etc.) we first define several important radiometric concepts, such as, light source intensity, surface illumination, surface brightness, image brightness and surface reflectance. Then, we tackle the challenging problem of shape from shading - recovering the shape of a surface from its shading in a single image. Next, we show that if multiple images of a scene of known reflectance are taken while changing the illumination direction, the surface normal at each scene point can be computed. This method, called photometric stereo, provides a dense surface normal map that can be integrated to obtain surface shape. Next, we discuss depth from defocus, which uses the limited depth of field of the camera to estimate scene structure. From a small number of images taken by changing the focus setting of the lens, a dense depth of the scene is recovered. Finally, we present a suite of techniques that use active illumination (the projection of light patterns onto the scene) to get precise 3D reconstructions of the scene. These active illumination methods are the workhorse of factory automation. They are used on manufacturing lines to assemble products and inspect their visual quality. They are also extensively used in other domains such as driverless cars, robotics, surveillance, medical imaging and special effects in movies.
Blended Learning Toolkit
Columbia University (via Coursera)
This class is designed for teaching and learning professionals, program directors, professors and others interested in implementing digital education programs at their institutions. It includes an overview of the history of digital education initiatives, suggestions on managing and digital education projects, and guides to the basics of blended learning, backwards course design, class filming, zoom use, and digital class delivery. This course builds on examples and best practices from Columbia University and peer institutions around the world, and draws on the more than 50 interviews conducted in the research of the Leveling the Learning Curve book project. It also shares insights, tips, and guides from leaders of top digital education programs at leading universities around the world such as Stanford, Penn, ASU, Dartmouth, Georgia Tech, UC Berkeley and many others, as well as leaders from the Digital Education divisions of the World Bank, UNDP, and PBS Learning Media. No prerequisite experience with digital education tools is required to be successful in this course. All you need is basic computer operation skills. The course utilizes presentation tools such as PowerPoint, video conferencing software Zoom and Panopto, and Canvas LMS. DIY tools such as ring light, microphone, webcam, and green screen are introduced but not required.
Attaining Higher Education
Columbia University (via edX)
Attaining Higher Education
Traitement antirétroviral pour lutter contre le VIH : mise en œuvre de l'approche « traiter tout le monde »
Columbia University (via edX)
Traitement antirétroviral pour lutter contre le VIH : mise en œuvre de l'approche « traiter tout le monde »
Fighting HIV with Antiretroviral Therapy: Implementing the Treat-All Approach
Columbia University (via edX)
Fighting HIV with Antiretroviral Therapy: Implementing the Treat-All Approach
Analytics in Python
Columbia University (via edX)
Analytics in Python
Data, Models and Decisions in Business Analytics
Columbia University (via edX)
Data, Models and Decisions in Business Analytics
Demand and Supply Analytics
Columbia University (via edX)
Demand and Supply Analytics
Marketing Analytics
Columbia University (via edX)
Marketing Analytics
MOS Transistors
Columbia University (via Coursera)
PLEASE NOTE: This version of the course has been formed from an earlier version, which was actively run by the instructor and his teaching assistants. Some of what is mentioned in the video lectures and the accompanying material regarding logistics, book availability and method of grading may no longer be relevant to the present version. Neither the instructor nor the original teaching assistants are running this version of the course. There will be no certificate offered for this course. Learn how MOS transistors work, and how to model them. The understanding provided in this course is essential not only for device modelers, but also for designers of high-performance circuits.
DELETE
Columbia University (via edX)
DELETE
Columbia Engineering Digital Marketing Boot Camp
Columbia University (via edX)
Columbia Engineering Digital Marketing Boot Camp
AI Boot Camp
Columbia University (via edX)
AI Boot Camp
Columbia Engineering Cybersecurity Boot Camp
Columbia University (via edX)
Columbia Engineering Cybersecurity Boot Camp
Columbia Engineering Data Analytics Boot Camp
Columbia University (via edX)
Columbia Engineering Data Analytics Boot Camp
Columbia Engineering FinTech Boot Camp
Columbia University (via edX)
Columbia Engineering FinTech Boot Camp
Columbia Engineering Product Management Boot Camp
Columbia University (via edX)
Columbia Engineering Product Management Boot Camp
Columbia Engineering Coding Boot Camp
Columbia University (via edX)
Columbia Engineering Coding Boot Camp
Columbia Engineering Technology Project Management Boot Camp
Columbia University (via edX)
Columbia Engineering Technology Project Management Boot Camp
Columbia Engineering UX/UI Boot Camp
Columbia University (via edX)
Columbia Engineering UX/UI Boot Camp
Indian & Tibetan River of Buddhism
Columbia University (via edX)
Indian & Tibetan River of Buddhism
Beyond Zoom Draft
Columbia University (via edX)
Beyond Zoom Draft
Course Design Essentials (Online)
Columbia University (via edX)
Course Design Essentials (Online)