This comprehensive Data Science course is your all-in-one guide to becoming a job-ready data professional — even if you’re starting from scratch.

You’ll go from beginner to advanced, learning everything from Python programming and data visualization to building real-world machine learning models. Through interactive lessons and hands-on projects, you’ll gain the practical skills and confidence to work with data, solve real business problems, and build a career in data science.

Whether you’re aiming to become a Data Scientist, Data Analyst, Machine Learning Engineer, or just want to use data more effectively in your current job — this course will give you the tools to succeed.

1. Python programming for data analysis

2. Working with data using NumPy, Pandas, Matplotlib, and Seaborn

3. Writing SQL queries to extract insights from databases

4. Statistics & probability for data-driven decision-making

5. Machine learning with Scikit-learn: regression, classification, clustering

6. Introduction to Deep Learning, NLP, and Time Series Analysis

7. Building and presenting real-world data science projects

8. Preparing for data science job interviews and building a professional portfolio

9. Python, Jupyter Notebooks, Google Colab

10. Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn

11. SQL (PostgreSQL or MySQL)

12. Real datasets from Kaggle, UCI, and open APIs

13. By the end of this course, you’ll have built a strong portfolio, mastered the essential data science workflow, and be ready to land your first job or freelance opportunity in the data space.

Who this course is for:

• Anyone looking to start a career in data science, machine learning, or AI.
• Students or graduates of any field (engineering, finance, biology, business, etc.) ready to transition into tech.