Data Science

Data Science & Machine Learning Masterclass

Transform your career with in-demand data science skills and hands-on ML projects.

4.9

892 students

16 weeks

Intermediate

About This Course

This masterclass offers a complete and carefully structured pathway to becoming a job-ready data science professional. You will begin by building strong foundations in Python, learning how to write clean, efficient code and work confidently with libraries such as NumPy and pandas for data cleaning and transformation. From there, you will explore statistics, probability and data visualization so that you can interpret datasets and communicate insights with clarity. The course then guides you step by step through the core machine learning algorithms used in industry, including regression, classification, clustering and ensemble methods, while teaching you how to evaluate models using the right metrics and validation strategies. Throughout the program, you will work on multiple real-world projects that mirror business use cases across domains such as finance, marketing and operations. By the end, you will understand the full data science workflow from raw data to deployed model and have a strong portfolio to showcase to recruiters and hiring managers.

What You'll Learn

✔Use Python for data analysis, cleaning and visualization

✔Implement core machine learning algorithms from scratch

✔Train, tune and evaluate classification & regression models

✔Work with real-world datasets and deploy simple ML pipelines

Course Syllabus

WEEK 1

Python for Data Analysis

•Python refresher: syntax, functions and modules
•NumPy for numerical computing
•Pandas for data cleaning and manipulation
•Exploratory data analysis with Jupyter

WEEK 2

Statistics & Data Visualization

•Descriptive statistics and probability distributions
•Hypothesis testing and confidence intervals
•Data visualization with Matplotlib and Seaborn
•Hands-on mini project: explore a real dataset

WEEK 3

Core Machine Learning

•Supervised vs unsupervised learning
•Regression and classification algorithms in scikit-learn
•Model evaluation: bias-variance, metrics and cross-validation
•Feature engineering and preprocessing pipelines

WEEK 4

Advanced ML & Intro to Deep Learning

•Ensemble methods: Random Forests and Gradient Boosting
•Clustering and dimensionality reduction
•Neural network basics with TensorFlow / Keras
•Capstone: build and evaluate an end-to-end ML project

Who Is This Course For?

✔Beginners in Data Science with basic Python knowledge

✔Engineers who want to move into ML roles

✔Analytics professionals upgrading from Excel to ML

Your Instructor

Dr. Rajesh Kumar

Data Science Lead

PhD in Machine Learning from MIT. Previously led data teams at Amazon and Microsoft.

4.9 rating

• 4,231 learners• 6 courses

₹499₹4499

Limited seats • Includes certification & lifetime access

This course includes

✔Real-world projects

✔Industry mentors

✔Job placement support

✔Cloud platform credits

✔30-day satisfaction guarantee

✔Flexible batch timings & mentor support