Online courses directory (684)

Learn critical concepts and practical methods to support research data planning, collection, storage and dissemination.

This course is an introduction to the theory and practice of financial engineering and risk management. We consider the pricing of derivatives, portfolio optimization and risk management and cast a critical eye on how these are used in practice. We will also feature some interview modules with Emanuel Derman .

Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data. #uwdatasci

Wavelets are localized basis functions, good for representing short-time events. The coefficients at each scale are filtered and subsampled to give coefficients at the next scale. This is Mallat's pyramid algorithm for multiresolution, connecting wavelets to filter banks. Wavelets and multiscale algorithms for compression and signal/image processing are developed. Subject is project-based for engineering and scientific applications.

Learn how to program all the major systems of a robotic car from the leader of Google and Stanford's autonomous driving teams. This class will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics. Extensive programming examples and assignments will apply these methods in the context of building self-driving cars. This course is offered as part of the Georgia Tech Masters in Computer Science. The updated course includes a final project, where you must chase a runaway robot that is trying to escape!

Communicating With Data has a distinctive structure and content, combining fundamental quantitative techniques of using data to make informed management decisions with illustrations of how real decision makers, even highly trained professionals, fall prey to errors and biases in their understanding. We present the fundamental concepts underlying the quantitative techniques as a way of thinking, not just a way of calculating, in order to enhance decision-making skills. Rather than survey all of the techniques of management science, we stress those fundamental concepts and tools that we believe are most important for the practical analysis of management decisions, presenting the material as much as possible in the context of realistic business situations from a variety of settings. Exercises and examples drawn from marketing, finance, operations management, strategy, and other management functions.

When developing chips it is essential that they get verified thoroughly because it is very hard or impossible to fix them once they have been manufactured. In this class, you will learn how to program verification environments that verify chip functionality efficiently, as well as understand and leverage automation such as constrained random test generation and improve code reuse leveraging a standardized methodology.

In an introduction to the basics of the famous Customer Development Process, Steve Blank provides insight into the key steps needed to build a successful startup. The main idea in this course is learning how to rapidly develop and test ideas by gathering massive amounts of customer and marketplace feedback. Many startups fail by not validating their ideas early on with real-life customers. In order to mitigate that, students will learn how to get out of the building and search for the real pain points and unmet needs of customers. Only with these can the entrepreneur find a proper solution and establish a suitable business model. Building a startup is not simply building an execution plan for a business model that the entrepreneur thinks will work, but rather, a search for the actual business model itself.

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research.

With existing data, you will develop skills in data analysis and basic statistics by exploring your own research question.

Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.

Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination. ***Note: Parts of this course are featured in the Machine Learning Engineer Nanodegree and the Data Analyst Nanodegree programs. If you are interested in AI, be sure to check out those programs as well!***

Try to picture yourself sitting down with your computer, ready to start developing a fully functional web application for the first time, available online for millions to use. “Where should I even begin? How long is this going to take me? Am I making any mistakes along the way?” The questions may leave you with an uneasy feeling that you will learn many lessons the hard way. In this intermediate course, Steve Huffman will teach you everything he wished he knew when he started building Reddit and, more recently, Hipmunk, as a lead engineer. Starting from the basics of how the web works, this course will walk you through core web development concepts such as how internet and browsers fit together, form validations, databases, APIs, integrating with other websites, scaling issues, and more; all of which form part of the knowledge it takes to build a web application of your own.

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

Want to learn how your radio works? Wondering how to implement filters using resistors, inductors, and capacitors? Wondering what are some other applications of RLC and CMOS circuits? This free circuit course, taught by edX CEO and MIT Professor Anant Agarwal and MIT colleagues, is for you.

The third and final online Circuits and Electronics courses is taken by all MITElectrical Engineering and Computer Science (EECS) majors.

Topics covered include: dynamics of capacitor, inductor and resistor networks; design in the time and frequency domains; op-amps, and analog and digital circuits and applications. Design and lab exercises are also significant components of the course.

Weekly coursework includes interactive video sequences, readings from the textbook, homework, online laboratories, and optional tutorials. The course will also have a final exam.

This is a self-paced course, so there are no weekly deadlines. However, all assignments are due by June 15, 2019, when the course will close.

Student Testimonials

“Brilliant course! It's definitely the best introduction to electronics in Universe! Interesting material, clean explanations, well prepared quizzes, challenging homeworks and fun labs.” - Ilya.

“6.002x will be a classic in the field of online learning. It combines Prof. Agarwal's enthusiasm for electronics and education. The online circuit design program works very well. The material is difficult. I took the knowledge from the class and built an electronic cat feeder.” - Stan 

Statistics One is a comprehensive yet friendly introduction to statistics.

In this course, you will explore several structured, risk management approaches that guide information security decision-making. 

Understanding how the brain works is one of the fundamental challenges in science today. This course will introduce you to basic computational techniques for analyzing, modeling, and understanding the behavior of cells and circuits in the brain. You do not need to have any prior background in neuroscience to take this course.