Ultimate Data Scientist Roadmap: Learn Skills, Courses & Resources

Data Scientist Roadmap

1. Mathematics and Statistics:

• Linear Algebra: Introduction to Linear Algebra by Gilbert Strang
• Calculus: Calculus by James Stewart
• Probability and Statistics: Introduction to Probability by Joseph K. Blitzstein and Jessica Hwang
• Multivariate Calculus: Multivariable Calculus by Grant Sanderson on Khan Academy
• Optimization: Convex Optimization by Stephen Boyd and Lieven Vandenberghe

2. Programming Skills:

• Python: Python for Data Science and Machine Learning Bootcamp on Udemy
• R: R Programming by Johns Hopkins University on Coursera

3. Data Manipulation and Analysis:

• Pandas (Python): Pandas Official Documentation
• NumPy (Python): NumPy Official Documentation
• SQL: SQL for Data Science on Coursera by University of California, Davis

4. Machine Learning:

• Introduction to Machine Learning: Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
• Deep Learning: Deep Learning Specialization on Coursera by Andrew Ng
• Scikit-learn (Python): Scikit-learn Official Documentation

5. Data Visualization:

• Matplotlib (Python): Matplotlib Official Documentation
• Seaborn (Python): Seaborn Official Documentation
• Tableau: Data Visualization and Communication with Tableau on Coursera by Duke University

6. Big Data Technologies:

• Apache Spark: Big Data Analysis with Spark on Coursera by University of California, Berkeley

7. Additional Skills:

• Version Control (Git): Pro Git by Scott Chacon and Ben Straub

8. Capstone Projects and Real-world Experience:

• Work on real-world datasets available on platforms like Kaggle, UCI Machine Learning Repository, etc.
• Build your portfolio showcasing your projects on platforms like GitHub.

9. Community Involvement:

• Join data science communities on platforms like Stack Overflow, Reddit, and LinkedIn.
• Participate in online forums and discussions to learn from others and share your knowledge.