Python, MySQL & Machine Learning Courses by Ratan Biswakarma

This comprehensive online Python, MySQL and Machine Learning course is ideal for learners who want to build strong practical skills in programming, data handling, analytics and AI-driven applications. Conducted by Ratan Biswakarma, the course is designed to take students from Python fundamentals through database management and into real-world machine learning workflows — with hands-on practice using industry-level datasets.

The program blends coding, databases, statistics, data processing and machine learning models so that learners gain a complete understanding of how modern data systems and intelligent applications are built. It is suitable for students, fresh graduates, working professionals and anyone interested in data science, AI or analytics.

Course Overview

The course begins with core Python programming, teaching you how to write clean, structured and efficient code. From there, you’ll explore data manipulation using NumPy and Pandas, followed by data visualization techniques using Matplotlib and Seaborn. Learners then move into SQL and MySQL fundamentals — including query writing and database optimization — before integrating Python with MySQL to build real-world data applications.

Once strong foundations are built, the course introduces Machine Learning concepts, including supervised and unsupervised learning, model building, evaluation techniques and project-based implementation. Learners will also explore supporting statistical and probability concepts essential for real-world analytics.

What Students Will Learn

Python Programming & Data Analysis

• Python basics: variables, loops, functions & OOP

• Working with files & real-world datasets

• NumPy & Pandas for data manipulation

• Data visualization using Matplotlib & Seaborn

MySQL & Databases

• Database fundamentals & SQL syntax

• Writing efficient queries: SELECT, JOIN, GROUP BY & Subqueries

• Database schema design & optimization

• Connecting Python with MySQL

Machine Learning & AI Foundations

• Statistics & probability concepts

• Data cleaning & feature engineering

• ML workflow & model development

• Supervised learning:
  Linear & Logistic Regression, Decision Trees, KNN

• Unsupervised learning:
  Clustering & Dimensionality Reduction

• Model validation & performance tuning

Practical Implementation

• Hands-on case studies

• Mini-projects throughout the course

• Final capstone project integrating Python + MySQL + ML

Teaching Method

This is a fully online, live-interactive training program. Sessions are structured for clarity and real-world application. Learners receive:

• Step-by-step explanation of concepts

• Practical coding demonstrations

• Query-writing and debugging support

• Regular exercises & guided practice

• Project-based learning for portfolio building

The approach prioritises understanding, application and confidence in using tools independently.

Why Learn with Ratan Biswakarma

The course structure is industry-relevant and skill-oriented, ensuring students gain both theoretical grounding and practical implementation capability. Teaching remains clear, approachable and supportive, helping learners progress at a comfortable pace while still being challenged to think analytically.

Benefits & Outcomes

By the end of the course, learners will be able to:

• Code confidently in Python

• Work with structured and unstructured datasets

• Design and query MySQL databases

• Build end-to-end data pipelines

• Implement Machine Learning models

• Understand AI workflows used in real-world systems

• Strengthen career readiness in data-driven fields

This program is highly suitable for those aspiring toward roles in data science, analytics, AI engineering, programming and software development.