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Machine Learning

Learn Machine Learning from basics to advanced with real-world projects, Python, algorithms, data preprocessing, model training, and AI applications. Perfect for beginners and professionals.

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Modules

Topics

159

Instructor

Rumman Ansari

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Course Overview

Everything a learner needs before starting the course.

Learning Outcomes

Understand the fundamentals of Machine Learning and AI
Build Machine Learning models using Python
Work with real-world datasets and perform data preprocessing
Learn supervised and unsupervised learning techniques
Train, test, and evaluate ML models effectively
Implement regression, classification, and clustering algorithms
Create practical AI and Machine Learning projects
Gain hands-on experience with Scikit-learn, Pandas, NumPy, and TensorFlow

Target Audience

Students who want to learn Machine Learning and Artificial Intelligence
Beginners interested in AI, ML, and Data Science
Software Developers looking to upgrade their technical skills
Python Programmers who want to build intelligent applications
Data Science Enthusiasts interested in real-world ML projects
Working Professionals planning to transition into AI and Machine Learning roles

Prerequisites

Basic computer knowledge
Basic understanding of mathematics and logic
Basic Python programming knowledge is recommended
No prior Machine Learning experience is required

Rumman Ansari

rummanansari6@gmail.com

Rumman Ansari is a Software Engineer, YouTuber, and Professional Educator with over a decade of experience in enterprise software development, technical architecture, and digital learning systems. He specializes in Microsoft Dynamics 365 Finance & Supply Chain Management, with deep expertise in X++ programming, SSRS reporting, and MB-500, MB-700 certification preparation.

As a content creator and educator, he runs a growing technical ecosystem through rummanansari.com and his YouTube channel, delivering structured, project-based learning to thousands of students worldwide. His content library includes nearly 1,000+ technical tutorials covering ERP development, web technologies (Java, Python, JavaScript, PHP, Bootstrap 5, etc.), database systems, and practical software engineering concepts.

He has professional experience as a System Engineer at Tata Consultancy Services (TCS) and Accenture, and holds an M-Tech in Computer Science. Combining real-world enterprise experience with simplified teaching methods, Rumman focuses on making complex technical concepts easy to understand, practical to implement, and scalable for career growth.

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Course Curriculum

Explore modules, topics, MCQs, questions, and coding items.

What is Machine Learning? Article

Types of Machine Learning Article

What is Supervised learning? Article

What is Unsupervised learning? Article

Machine Learning vs Artificial intelligence Article

Machine Learning Tutorial Article

History of Machine Learning Article

Reinforcement Learning Article

Machine Learning vs Deep Learning Article

Applications of Machine Learning Article

Machine Learning Workflow Article

Advantages and Limitations of Machine Learning Article

Structured Data Classification Article •1 Q

Hands on Article

Introduction to Classification Article

Binary Classification Article

Multi-Class Classification Article

Logistic Regression Article •1 MCQ

Decision Tree Classifier Article

Random Forest Classifier Article

K-Nearest Neighbors (KNN) Article

Support Vector Machine (SVM) Article

Naive Bayes Algorithm Article

Hands-on Classification Project Article

Unstructured Data Classification Article •1 Q

Introduction to Unstructured Data Article

Text Classification Article

Image Classification Article

Audio Classification Article

Natural Language Processing Basics Article

Tokenization Article

Stop Words Removal Article

Stemming and Lemmatization Article

TF-IDF Vectorization Article

Sentiment Analysis Article

Hands-on NLP Project Article

Introduction to Python Article

Variables and Data Types Article

Operators and Expressions Article

Loops and Conditional Statements Article

Functions in Python Article

NumPy Basics Article

Pandas Basics Article

Matplotlib for Visualization Article

Seaborn for Data Visualization Article

Jupyter Notebook Introduction Article

Linear Algebra Basics Article

Scalars, Vectors, and Matrices Article

Matrix Operations Article

Probability Basics Article

Statistics Fundamentals Article

Mean, Median, Mode Article

Variance and Standard Deviation Article

Correlation and Covariance Article

Calculus for Machine Learning Article

Gradient Descent Article •15 MCQ

What is Data Preprocessing? Article

Handling Missing Data Article

Feature Scaling Article

Normalization vs Standardization Article

Encoding Categorical Data Article

Train-Test Split Article

Feature Engineering Article

Handling Outliers Article

Data Cleaning Techniques Article

Dimensionality Reduction Article

Introduction to Regression Article

Linear Regression Article •1 MCQ

Multiple Linear Regression Article

Polynomial Regression Article

Ridge Regression Article

Lasso Regression Article

Regression Evaluation Metrics Article

Hands-on Regression Project Article

What is Clustering? Article

K-Means Clustering Article

Hierarchical Clustering Article

DBSCAN Clustering Article

Elbow Method Article

Silhouette Score Article

Customer Segmentation Project Article

Introduction to Association Rules Article

Apriori Algorithm Article

Market Basket Analysis Article

FP-Growth Algorithm Article

Accuracy Article

Precision Article

Recall Article

F1 Score Article

Confusion Matrix Article

ROC Curve Article

AUC Score Article

Cross Validation Article

Bias vs Variance Article

Overfitting and Underfitting Article

Introduction to Deep Learning Article

Artificial Neural Networks Article

Activation Functions Article

Forward Propagation Article

Backpropagation Article

TensorFlow Introduction Article

Keras Introduction Article

Building First Neural Network Article

Introduction to Computer Vision Article

Image Processing Basics Article

Convolutional Neural Networks (CNN) Article

Image Recognition Article

Object Detection Article

Face Recognition Project Article

NLP Overview Article

Bag of Words Article

Word Embeddings Article

RNN Basics Article

LSTM Networks Article

Transformer Models Article

Chatbot Development Article

Introduction to Time Series Article

Time Series Components Article

ARIMA Model Article

Forecasting Techniques Article

Stock Price Prediction Project Article

Introduction to Recommendation Systems Article

Content-Based Filtering Article

Collaborative Filtering Article

Movie Recommendation System Project Article

Introduction to Reinforcement Learning Article

Agent and Environment Article

Q-Learning Article

Reward Function Article

Real-World Applications Article

House Price Prediction Article

Spam Email Detection Article

Fake News Detection Article

Image Classification Project Article

Customer Churn Prediction Article

Sales Forecasting Article

Chatbot Project Article

Introduction to Model Deployment Article

Saving and Loading Models Article

Flask for ML Deployment Article

FastAPI for ML APIs Article

Deploying ML Model on Cloud Article

Docker Basics for ML Article

What is MLOps? Article

ML Pipeline Article

Model Monitoring Article

CI/CD for ML Article

Version Control for Models Article

Introduction to Generative AI Article

What are Large Language Models? Article

Prompt Engineering Article

Fine-Tuning Basics Article

Retrieval-Augmented Generation (RAG) Article

AI Agents Introduction Article

AI Ethics Article

Bias in Machine Learning Article

Explainable AI Article

Data Privacy Article

Responsible AI Practices Article