How to Learn Data Science, ML, Programming
Offered By: James Briggs via YouTube
Course Description
Overview
Discover effective strategies for learning data science, machine learning, and programming in this informative 17-minute video. Explore five key approaches, including balancing theory and application, understanding the learning curve, choosing between courses and projects, leveraging open-source resources, and honing writing skills. Gain insights on following your interests and receive valuable final tips to enhance your learning journey in these technical fields.
Syllabus
Intro
Scale of Theory vs. Applied
Shape of Learning
Courses vs. Projects
Open Source
Writing
Following Interests
Final Notes
Taught by
James Briggs
Related Courses
Computer Vision: The FundamentalsUniversity of California, Berkeley via Coursera Programming Languages
University of Virginia via Udacity Learn to Program: Crafting Quality Code
University of Toronto via Coursera Computational Photography
Georgia Institute of Technology via Coursera Algorithms: Design and Analysis, Part 2
Stanford University via Coursera