What You'll Get

✓ A structured 6–9 month learning path from Python basics to advanced machine learning and deep learning.
✓ Strong foundation in statistics and probability to confidently interpret data and validate models.
✓ Hands-on experience with NumPy, Pandas, and data cleaning techniques for real-world datasets.
✓ Ability to perform exploratory data analysis (EDA) and build clear, insight-driven visualizations with Matplotlib, Seaborn, Plotly, and Tableau.
✓ Practical skills to design, train, and evaluate core ML models like regression, classification, decision trees, random forests, SVMs, and ensembles.
✓ Deep understanding of neural networks, CNNs, RNNs/LSTMs, and transfer learning using TensorFlow.

Course Curriculum

10 modules • 72 lessons

1. Python Programming Fundamentals

8 lessons

2. Statistics and Probability for Data Science

7 lessons

3. Data Manipulation and Analysis

8 lessons

4. Data Visualization

7 lessons

5. Machine Learning Fundamentals

8 lessons

+ 5 more modules

About This Course

This intensive 6–9 month Data Science & Machine Learning Program is designed for

aspiring Data Scientists, ML Engineers, and Analytics Professionals who want to move beyond theory and build real, production-ready solutions.

You will master: python, statistics, data wrangling, visualization, machine learning, deep learning, NLP, big data cloud tools through 10 industry-aligned modules and an end-to-end capstone. The program blends structured video lessons, guided reading, quizzes, and hands-on projects so you build a strong mathematical foundation while learning how to ship models that work in the real world.​


By the end, you will be able to clean and explore large datasets, build and evaluate ML models, design deep learning architectures, implement NLP pipelines, and deploy solutions using Spark and cloud platforms. This makes you ready for high-growth roles such as Data Scientist, ML Engineer, and Applied AI Analyst with salaries typically starting from mid to high six figures annually.