Data science is one of the most exciting and well-paying careers in tech. Companies across every industry need professionals who can extract insights from data, build predictive models, and drive data-driven decisions.
The average data scientist salary in 2025 is $120,000, with senior roles exceeding $200,000. Even entry-level data analysts can earn $60,000-$80,000. Best of all, you can learn the skills for free.
What is Data Science?
Data science combines programming, statistics, and domain expertise to extract meaningful insights from data. It includes:
- Data Analysis: Exploring and understanding data
- Data Visualization: Communicating findings visually
- Machine Learning: Building predictive models
- Statistical Analysis: Testing hypotheses and making inferences
Start Data Science Free
Access our complete data science bootcamp with Python projects!
Start Learning ?Essential Skills for Data Science
1. Python Programming
Python is the primary language for data science. Learn:
- Basic syntax and data structures
- NumPy for numerical computing
- Pandas for data manipulation
- Matplotlib and Seaborn for visualization
2. Statistics and Probability
Foundation for all data science work:
- Descriptive statistics (mean, median, mode)
- Probability distributions
- Hypothesis testing
- Correlation and regression
3. SQL and Databases
Most business data lives in databases:
- SELECT, JOIN, GROUP BY, WHERE
- Subqueries and CTEs
- Database design basics
4. Machine Learning
Build predictive models:
- Supervised learning (classification, regression)
- Unsupervised learning (clustering, dimensionality reduction)
- Scikit-learn library
- Model evaluation and validation
Data Science Learning Path
Month 1-2: Python and Statistics
- Complete Python basics
- Learn NumPy and Pandas
- Study statistics fundamentals
- Practice with small datasets
Month 3: SQL and Data Visualization
- Master SQL queries
- Create visualizations with Matplotlib
- Learn Seaborn for statistical plots
Month 4-5: Machine Learning
- Andrew Ng's Machine Learning course
- Scikit-learn tutorials
- Build ML projects
Month 6+: Portfolio Projects
- Kaggle competitions
- Real-world datasets
- End-to-end projects
Data Science Toolkit
Download our free Python cheatsheets for data science!
Download Free ?Best Free Resources
Courses
- IBM Data Science Certificate (Coursera): Comprehensive program
- Google Data Analytics (Coursera): Beginner-friendly
- Andrew Ng's ML Course: Gold standard for ML
- Kaggle Learn: Short, practical courses
Practice Platforms
- Kaggle: Datasets, competitions, notebooks
- HackerRank: SQL and Python practice
- DataCamp: Interactive exercises
Building Your Portfolio
Projects employers want to see:
- Exploratory data analysis on real datasets
- Predictive modeling (house prices, customer churn)
- Data visualization dashboards
- Natural language processing projects
- Kaggle competition submissions
Career Paths in Data Science
- Data Analyst: $60K-90K - Entry point
- Data Scientist: $90K-150K - Core role
- ML Engineer: $120K-200K - Production ML
- Data Engineer: $100K-160K - Data infrastructure
Data science is accessible to anyone willing to learn. Start with Python, build projects, and grow your skills every day. The journey begins with a single line of code!