Free online courses with certificate

Supervised Machine Learning: Regression Algorithms with Python

Master supervised machine learning regression techniques using Python and Scikit-Learn. Learn Simple and Multiple Linear Regression, Gradient Descent, Regularization, and Decision Tree Regression. Explore model building, prediction, and optimization through hands-on implementation and real-world projects, including Rainfall Prediction. Develop practical skills to build regression models and predict continuous numerical values.

Mathematics for Data Science: Linear Algebra & Calculus

Build a strong mathematical foundation for Data Science and Machine Learning. Learn essential concepts of linear algebra, matrices, vectors, derivatives, gradients, and optimization techniques. Understand how mathematical principles power data analysis, machine learning algorithms, and AI models through practical examples and real-world applications.

Ensemble ML Techniques & Applications

Master advanced ensemble learning techniques, including Bagging, Boosting, Random Forest, AdaBoost, Gradient Boosting, XGBoost, and Stacking. Learn to combine multiple machine learning models to improve prediction accuracy, optimize performance, and solve real-world data science problems through practical Python projects.

Supervised Learning Classification

Machine Learning Fundamentals

This course introduces the core principles, algorithms, and practical applications of machine learning. Learners explore supervised and unsupervised learning, data preprocessing, regression, classification, clustering, model evaluation, and hyperparameter tuning. Through hands-on exercises using Python, Pandas, NumPy, Matplotlib, and Scikit-learn, students develop the skills needed to build, train, evaluate, and improve machine learning models for real-world problems.

Regression Foundations with Python

Learn the fundamentals of regression analysis using Python in this beginner-friendly course. Understand how regression models work, explore the relationship between variables, and learn how to build predictive models using real-world datasets. This course covers simple linear regression, data preparation, model training, prediction, and performance evaluation using popular Python libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. By the end of this course, you will be able to build and evaluate basic regression models and apply regression techniques to practical data analysis and machine learning problems.

Python Flask & REST API Development – From Basics to Real-World Projects

Learn how to build powerful web applications and RESTful APIs using Python and Flask. This course covers the fundamentals of Flask, routing, HTTP methods, request and response handling, JSON data processing, and REST API development. You will learn how to create API endpoints, perform CRUD operations, connect databases, validate incoming data, handle errors, and implement authentication to build secure and scalable backend applications. Through practical examples and hands-on projects, you will gain the skills needed to develop backend services and APIs that can integrate with frontend applications, mobile apps, and other software systems.

Data Modelling, ETL & Data Warehousing for Analysts

Flask For Web Development

Learn to build dynamic, scalable, and secure web applications using **Flask**, Python’s lightweight web framework. This course covers routing, templates, forms, database integration, user authentication, REST APIs, and application deployment. Gain hands-on experience through practical projects and develop the skills to create professional, real-world web applications using Python and Flask.

Mastering Linear Regression: Theory & Implementation

This course provides a structured understanding of Linear Regression, covering fundamental theory, assumptions, model building, evaluation metrics, diagnostics, and optimization techniques. It prepares learners to build accurate, interpretable, and reliable regression models using practical implementation in Python and R.

Advanced Microsoft Excel for Data Analysis and Automation

This course provides a comprehensive understanding of Microsoft Excel, covering essential skills, advanced formulas, data management, visualization, PivotTables, automation using VBA, and integration with Power BI. It equips learners with practical techniques to analyze data efficiently, build dashboards, and automate workflows for real-world business and analytical tasks.

Mastering Random Forest Algorithms

Learn the fundamentals of the Random Forest algorithm, including decision trees, ensemble learning, bagging techniques, feature selection, model training, and performance evaluation. Explore real-world machine learning applications, classification and regression workflows, and practical implementation using Python and modern data science tools.

Responsive Web Design with Bootstrap

Bootstrap is a front-end framework that helps create responsive and mobile-first websites quickly. It provides pre-designed components, grids, and utilities, making web design faster, consistent, and efficient.

Python OOP Programming

This Python Object-Oriented Programming (OOP) course is designed to help you transition from writing basic scripts to building scalable, professional-grade software. We focus on the core principles that drive modern application development, ensuring you gain the "industry-ready" logic needed for complex projects.

Foundation Course in Generative AI

Learn the fundamentals of Generative AI and modern AI tools through practical examples and hands-on activities. This course covers AI basics, prompt engineering, AI chatbots, content generation, image generation, automation concepts, and real-world applications using popular AI platforms and tools. Ideal for students, educators, professionals, and beginners exploring the world of Artificial Intelligence.

Digital Marketing for Business Growth

Learn Digital Marketing from basics to advanced with practical strategies and real-world tools. This course covers SEO, social media marketing, Google Ads, content marketing, email marketing, analytics, branding, and online advertising techniques to help businesses grow their digital presence and reach targeted audiences effectively.

Python Flask and REST API Development

Learn web application and REST API development using Python and Flask. This course covers routing, templates, database integration, authentication, JSON handling, API creation, and backend development with hands-on projects. Ideal for students and developers who want to build modern web applications and RESTful services.

MySQL for Web and Application Development

Learn MySQL Programming from basics to advanced with hands-on database training. This course covers database design, SQL queries, table creation, joins, functions, stored procedures, triggers, and database management techniques. Students will gain practical experience in managing and developing databases for web and software applications using MySQL.

ML Model Evaluation & Hyperparameter Tuning

Learn to evaluate machine learning models, choose the right metrics, and tune hyperparameters using cross-validation, grid search, and random search. Build practical Python skills to detect overfitting, prevent data leakage, and compare models fairly.

Data Cleaning and Pre-processing

Master essential data cleaning and preprocessing techniques using Python and Pandas. Learn to handle missing values, remove duplicates, fix inconsistent data, detect outliers, and transform raw datasets into structured, analysis-ready data. Explore feature scaling, encoding, and preprocessing techniques through practical exercises and real-world datasets to prepare data for accurate analysis and Machine Learning models.