Complete Python Data Science & Machine Learning Bootcamp
About This Course
The Complete Python Data Science & Machine Learning Bootcamp is a comprehensive, beginner-to-advanced course designed to help you master the complete data science workflow using Python.
You’ll begin with Python programming, learning core concepts and best practices to write clean, efficient, and production-ready code. Next, you’ll explore Exploratory Data Analysis (EDA), where you’ll learn how to clean, analyze, and visualize data to uncover insights, trends, and patterns.
A strong emphasis is placed on Statistics, enabling you to understand the mathematical and statistical foundations behind data analysis and machine learning models. You’ll then move into Machine Learning, where you’ll learn essential algorithms, model evaluation techniques, and how to apply them to solve real-world problems.
By the end of this bootcamp, you’ll have the confidence to work with real datasets, build intelligent models, and apply data-driven thinking in practical scenarios preparing you for roles in Data Science, Machine Learning, and Analytics.
Learning Objectives
Material Includes
- Structured learning modules
- Topic-wise quizzes
- Full project source code
- Course completion certificate
Requirements
- Basic computer knowledge and willingness to learn
- No prior programming or data science experience required
- A laptop or desktop with internet access
- Interest in Python, Data Science, and Machine Learning
Target Audience
- Beginners who want to start a career in Data Science and Machine Learning with Python
- Students and fresh graduates aiming for Data Analyst, Data Scientist, or ML Engineer roles
- Working professionals looking to upskill or transition into data-driven roles
- Software engineers and developers looking to enhance their profiles with Data Science and Machine Learning skills.
Curriculum
Getting Started
Introduction to Python4:58
Course Materials & Solutions
Python Basics
Data Structures in Python
Logic Building in Python
File Management & OOPS
Scientific Computing
Data Visualization
Statistics & Data Foundations
Sampling & Descriptive Analytics
Variability, Bias & Statistical Logic
Probability & Bayesian Thinking
Probability Distributions & Normal Curve
Covariance & Correlation Analysis
Hypothesis Testing & Statistical Inference
Data Analytics & EDA Overview
EDA Process & Data Preparation
Feature Scaling & Outlier Treatment
Data Types & Analysis Techniques
Feature Engineering
EDA Case Study & Reporting
Introduction to Machine Learning
Pre-Requisites
Regression
Classification
Ensemble Learning
Clustering
Feature Engineering
Hyper Parameter Optimization
Deployment
Conclusion
Earn a certificate
Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.
Your Instructors
Dr. Satyajit Pattnaik
Dr. Satyajit Pattnaik is a distinguished Data and AI professional based in Hong Kong, widely recognized for his ability to transform complex data into meaningful, actionable insights. With a thriving community of over 35,000 LinkedIn followers and 105,000+ YouTube subscribers, he leverages his deep expertise in generative AI, machine learning, deep learning, and analytics to mentor the next generation of data analysts, data scientists, and AI engineers.
A graduate of the Swiss School of Business and Management, Dr. Pattnaik has led cutting-edge research in voice-based patient classification, delivering outstanding accuracy and advancing the field of AI-driven healthcare solutions.
Over the course of his career, he has trained more than 200,000+ professionals, both through live sessions and his educational YouTube content, where he shares practical knowledge, industry insights, and advanced tutorials. A strong advocate for the power of generative AI, he has conducted numerous workshops designed to equip learners with the skills needed to thrive in the evolving tech landscape. Driven by a passion for education and community building, Dr. Pattnaik remains a trusted guide and inspiration for anyone aiming to elevate their expertise in data analytics and artificial intelligence.