Hi there!!
Welcome to my Data Science Hub!
I created this hub to help beginners get started with data science. The field is oftentimes overwhelming and complex, given that it combines multiple field together. This hub offers a special data science roadmap to help guide you and links my other book-sized interactive roadmaps.
Below are 100+ free courses for learning data science, SQL, data analytics, machine learning and AI. Dive in!
The General Data Science Roadmap
1. Programming (Python)
- Learn the Basics: Start with Python syntax, data types, variables, basic operators, and control flow (conditions and loops).
- Advanced Python Concepts: Understand list comprehensions, lambda functions, classes and objects, and module imports.
- Libraries and Tools: Get familiar with essential libraries like NumPy for numerical data, Pandas for data manipulation, and Matplotlib for basic plotting.
- Practice Coding Regularly: Work on small projects or exercises to enhance your coding skills.
- Debugging and Testing: Learn how to use debugging tools and write tests to check the correctness of your code.
- Environment Management: Use virtual environments (like venv or conda) to manage dependencies.
- Read Python Code: Study code from others in GitHub repositories or open-source projects.
- Participate in Coding Challenges: Engage in platforms like LeetCode, HackerRank to improve problem-solving skills.
- Project: Simple Python Project: Create a basic application like a calculator or a simple game to consolidate your learning.
2. Probability, Statistics, Linear Algebra
- Probability Theory: Learn about probability rules, random variables, distributions, and Bayesian thinking.
- Descriptive Statistics: Understand measures of central tendency, dispersion, correlation, and data summarization.
- Inferential Statistics: Get into hypothesis testing, confidence intervals, p-values, and ANOVA.
- Regression Analysis: Understand linear and logistic regression models.
- Linear Algebra: Focus on vectors, matrices, matrix operations, and eigenvalues/vectors.