There is such a wealth of resources out there online to help you learn Data Science for FREE. Lecture Videos, Lecture Notes, and Instructor Insights.Mathematics of Big Data and Machine Learning Problem Sets with Solutions, Exams with Solutions, Lecture Notes, and Programming Assignments with ExamplesĦ.Lecture Videos, Problem Sets, Lecture Notes, and Programming Assignmentsĥ.Introduction to Computer Science and Programming in Python Problem Sets, Lecture Notes, Lecture Videos, and Programming Assignments with ExamplesĤ.Problem Sets, Lecture Videos, and Exams with Solutionsģ.Introduction to Computer Science and Programming Online Textbook, Lecture Videos, Lecture Notes, Problem Sets, and ExamsĢ.They have a list of courses, I will provide a few that can get you started: You can search for anything you want, and then once you click on the course there will be a left drop-down menu that will provide the syllabus and other resources. They share Open Educational Resources (OER) to help people learn, increase their knowledge, and change their lives, for FREE! MIT is a leading institute for learning and in 2001, the university launched a platform called OpenCourseWare. There are lectures available from 2017, giving you an insight into how Deep Learning has evolved over the years. They offer a course called Deep Learning and Artificial Intelligence, which dives into the foundations of deep learning, autonomous vehicles, and AI. Massachusetts Institute of Technology is a private land-grant research university in Cambridge. Massachusetts Institute of Technology (MIT) - Deep Learning To ensure you understand the lecture slides and notebooks, make sure your Data Science skills are intact.ĥ. This course is for those who are proficient in Data Science and have more interest in Deep Learning. This course will cover the basics of Deep Learning, with a focus on applications. The Institut Polytechnique De Paris offers a course called Master Year 2 Data Science. Institut Polytechnique De Paris - Data Science You can then use the following link to work:Ĥ. If you plan to work through the materials independently, you can make an account at Gradescope and enroll using this code: 93PWD8. It has a specific emphasis on statistics and the decision-theoretic modeling paradigm. The course goes through the basic understanding and techniques of intelligent computer systems. Other aspects that are covered are GitHub, unit testing, and more.īerkeley University offers a course called CS 188 - Introduction to Artificial Intelligence. He covers the foundations of machine learning, from data exploration, data cleaning, model evaluation, and tuning. He is also a lecturer at Columbia University. Muller, who is one of the developers of the Python machine learning library Scikit-learn. The Applied Machine Learning course was created by Andreas C. Columbia Engineering - Applied Machine Learning
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