AI/ML Programming Course
The AI/ML Programming Course is designed to help you build intelligent, data-driven applications. You will learn Python programming, data analysis, and core machine learning concepts from scratch. The course covers supervised and unsupervised learning techniques used in real-world systems. You’ll gain hands-on experience with popular libraries like NumPy, Pandas, and Scikit-Learn. Advanced modules introduce deep learning, neural networks, and model optimization. By the end of the course, you’ll be ready to work on real AI/ML projects with confidence.
- 900 Hours (2 hours/day x 6 days/week x 75 weeks) OR at your own pace
- Hindi, English
- Learn & Get Certified
- Basic & Intermediate
- Hands-On Training
Online Course Fees
Offline Course Fees
About this course
The AI/ML Programming Course is designed to equip you with the skills to build intelligent systems using data, statistical methods, and cutting-edge machine learning models. Through practical code examples, real datasets, and guided projects, you’ll learn how to solve real-world problems using Python and advanced AI techniques.
This course bridges the gap between theory and practice — from basic Python programming to advanced neural networks and deep learning models that power applications like image recognition, natural language processing (NLP), predictive analytics, and more.
What you'll learn
Upon completing this course, you will be able to:
- Write efficient Python code for data processing and model development.
- Understand the mathematics behind key ML algorithms like regression, classification, and clustering.
- Build and evaluate supervised and unsupervised machine learning models.
- Develop deep learning models using frameworks like TensorFlow or PyTorch.
- Work with real-world datasets and deploy models in practical projects.
- mplement techniques for feature extraction, optimization, and performance tuning.
Course Content
Module 1: Introduction to AI & Machine Learning
Understand AI, ML, and Deep Learning fundamentals
History, scope, and applications across industries
Types of ML: Supervised, Unsupervised, Reinforcement Learning
Module 2: Python for AI/ML
Python programming basics — variables, loops, functions
Data structures and control flow
Libraries: NumPy, Pandas, Matplotlib, Seaborn
Module 3: Data Preprocessing & Feature Engineering
Data cleaning, handling missing values
Exploratory Data Analysis (EDA)
Feature selection and transformation
Module 4: Supervised Learning Algorithms
Linear Regression, Logistic Regression
Decision Trees, Random Forests, Support Vector Machines
Model evaluation metrics & cross-validation
Module 5: Unsupervised Learning
Clustering: K-Means, Hierarchical
Principal Component Analysis (PCA)
Dimensionality reduction basics
Module 6: Deep Learning & Neural Networks
Introduction to Neural Networks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs) and LSTM
Using TensorFlow or PyTorch
Module 7: Advanced Topics
Natural Language Processing (NLP) basics
Introduction to Reinforcement Learning
Model deployment foundations
Capstone Project & Real-World Use Cases
Build end-to-end ML solution on real datasets
Deploy a basic ML model via web or cloud
Showcase projects for portfolio
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With over a decade of experience, our mission is to produce future-ready skilled resources.
Job Opportunities
Completing this AI/ML course prepares you for roles such as:
Machine Learning Engineer – Build and deploy ML models.
Data Scientist – Use data analytics and predictive modeling.
AI Developer – Develop intelligent applications using AI libraries.
Deep Learning Specialist – Implement neural networks for vision & language tasks.
Business Analyst (AI Focus) – Translate data insights into business decisions.
Demand for these roles continues to grow as AI adoption expands across sectors.
Frequently asked questions
Q: Do I need programming experience to start?
Basic programming knowledge helps, but this course covers Python from fundamental to advanced levels.
Q: Is there a certification?
A: Yes — a professional AI/ML certificate upon successful course completion.
Q: Will I get job support?
A: The course includes resume review, interview prep, and project showcase guidance.
Q: How is training delivered?
A: You can learn online through interactive sessions or at your own pace via self-paced modules.
