Machine Learning for Beginners: Build Projects

Course Duration:

5 Weeks

Starting From:

1st June

Our comprehensive course in Artificial Intelligence and Machine Learning is perfect for those looking to learn machine learning from scratch. Designed for beginners and intermediate learners, it covers everything from the introduction to machine learning and deep learning AI to advanced applied machine learning techniques.

Through hands-on machine learning projects, you'll explore real-world applications like fraud detection and anomaly detection using machine learning examples. The course also introduces quantum machine learning, MATLAB machine learning integration, and mathematics for machine learning to build strong conceptual clarity.

You’ll gain in-demand skills in data science and machine learning, working with tools and techniques to build smart AI systems. From machine learning for dummies to practical implementations, this course is tailored for anyone eager to master AI machine learning.

By the end, you’ll be equipped to build your own machine learning programs and pursue a thriving career in deep learning, AI, and beyond.

Module 1: Python for Machine Learning

Python Basics: Data Types, Loops, Functions
File Handling & Data Structures
Project: Titanic Dataset Analysis

Module 2: Introduction to Machine Learning

Types of ML (Supervised & Unsupervised)
Setting Up ML Environment (Jupyter Notebook, Libraries)

Module 3: Data Wrangling & Preprocessing

Handling Missing Data, Feature Scaling, Encoding
Data Visualization & Dimensionality Reduction
Project: House Price Prediction

Module 4: Regression & Classification Algorithms

Linear Regression (MSE, RMSE, R²)
Logistic Regression (Precision, Recall, F1 Score)
Projects: House Price & Heart Disease Prediction

Module 5: Core Classification & Ensemble Models

Decision Trees, Random Forest, k-NN, SVM, Naïve Bayes
Project: Breast Cancer Prediction

Module 6: Model Evaluation & Tuning

Train-Test Split, Bias-Variance Tradeoff
Hyperparameter Tuning (Grid Search, Random Search)

Module 7: Clustering & Unsupervised Learning

K-Means, Hierarchical Clustering, DBSCAN
Project: Customer Segmentation

Module 8: Capstone Project – Hand Digit Image Classification

End-to-End ML Project (Data Preprocessing, Model Training, Deployment)

Module 9: Generative AI & LLMs

Transformer Architecture, Prompt Engineering, RAG
Project: Personalized Chatbot using LLMs & Gradio

Gain expertise in Machine Learning using Python and R programming languages.

Make accurate predictions and perform powerful data analysis for real-world applications.

Build robust and scalable Machine Learning models for both business and personal use.

Apply ML techniques to drive business value and create intelligent automation.

Learn how to choose the right ML model for different types of problems and datasets.

Combine multiple ML models using ensemble methods to solve complex challenges effectively.
Basic programming knowledge (Python recommended)

Access to coding exercises, datasets, and ML templates

Participation in community discussions & peer collaboration

Price -

₹ 1999.00

₹ 3998.00

50% OFF

12 hours left to avail at this price !

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Doubt Sessions

Project Hands - on

Certification on Course Completion

Recorded Sessions

Evening Classes