Neutrixtech

Logo
SCHEDULE CALL

Artificial Intelligence (AI) Course

Explore AI concepts using Python, machine learning models, datasets, and real-world use cases. Build intelligent systems step by step with hands-on projects.

Why Choose AI Training at Neutrixtech?

  • Beginner-friendly with step-by-step guidance

  • Covers both Python + AI/ML concepts

  • Hands-on projects with real datasets

  • Industry-ready syllabus aligned with AI jobs

  • Certificate

  • Career & freelancing guidance included

Apply Now
AI/ML

Course Modules

Introduction to Artificial Intelligence

  • What is AI? History & applications

  • AI vs Machine Learning vs Deep Learning

  • Real-world examples: chatbots, recommendation engines, self-driving cars

Python for AI

  • Python basics (variables, data types, loops, functions)

  • Libraries for AI: NumPy, Pandas, Matplotlib, Seaborn

  • Working with datasets (CSV, JSON, APIs)

  • Data visualization techniques

Data Preprocessing & Cleaning

  • Handling missing data

  • Normalization & standardization

  • Feature selection & extraction

  • Splitting datasets (train/test)

Machine Learning Basics

  • Introduction to ML algorithms

  • Supervised vs Unsupervised learning

  • Regression models (Linear & Logistic Regression)

  • Classification (Decision Trees, KNN, Naïve Bayes)

  • Clustering (K-Means, Hierarchical Clustering)

Advanced AI Concepts

  • Neural networks & deep learning basics

  • Natural Language Processing (NLP)

  • Computer vision fundamentals

  • Reinforcement learning overview

AI Tools & Frameworks

  • Scikit-Learn (ML models)

  • TensorFlow & PyTorch (intro to deep learning)

  • OpenCV (image processing basics)

  • Hugging Face Transformers (intro to NLP)

Real-World AI Applications

  • Chatbots & virtual assistants

  • AI in eCommerce (recommendation systems)

  • AI in Healthcare (disease prediction models)

  • AI in Finance (fraud detection basics)

Projects & Case Studies

  • Build a Spam Email Classifier

  • Movie Recommendation System

  • Handwritten Digit Recognition (MNIST dataset)

  • Customer Segmentation using Clustering

Career Opportunities

  • AI Engineer (Entry Level)

  • Machine Learning Engineer

  • Data Analyst / AI Analyst

  • AI Research Assistant

  • Python Developer (AI Focused)

Course Duration & Mode

  • Duration: 6-12 Months (depending on batch schedule and learning pace)

  • Mode: Offline / Online

  • Projects: Live website design projects included

  • Assessment: Portfolio and final project evaluation

  • Internship / Training Certificate
Scroll to Top