Artificial Intelligence Course in Jaipur – AI, Machine Learning & Generative AI Training
Build practical AI skills with Groot Academy’s Artificial Intelligence Course in Jaipur. Learn Python, mathematics and statistics for AI, data preparation, machine learning, deep learning, natural language processing, computer vision, Generative AI, model deployment and responsible AI through hands-on exercises and live projects.
What You Will Learn
- Python programming and data handling for Artificial Intelligence
- Mathematics, statistics and probability fundamentals for AI
- Data preprocessing and feature engineering
- Supervised and unsupervised machine learning algorithms
- Neural networks and deep learning with TensorFlow and Keras
- Natural Language Processing and text classification
- Computer vision and image recognition fundamentals
- Generative AI, Large Language Models and prompt engineering concepts
- AI model APIs, deployment and monitoring concepts
- AI ethics, responsible AI and live capstone projects
Related Courses
Strengthen your AI learning path with our Machine Learning Course in Jaipur, Data Science Course in Jaipur, Generative AI Course in Jaipur, Python Programming Course in Jaipur and Data Analytics Course in Jaipur.
Practical Learning and Career Support
Build your portfolio through Live Project Training, explore Internship Programs and learn about Placement Assistance.
Frequently Asked Questions
Is this Artificial Intelligence course suitable for beginners?
Yes. The course begins with Python, mathematics and data fundamentals before progressing toward machine learning, deep learning and Generative AI concepts.
Which technologies and tools are covered?
The course includes Python, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, NLP workflows, OpenCV concepts and AI deployment fundamentals.
Are practical projects included?
Yes. Students work on prediction, NLP, computer vision, Generative AI and end-to-end Artificial Intelligence projects.
Curriculum
- 15 Sections
- 150 Lessons
- 10 Weeks
- Introduction to Artificial Intelligence10
- 1.1Introduction to Artificial Intelligence
- 1.2History and Evolution of AI
- 1.3Types of Artificial Intelligence
- 1.4Narrow AI vs General AI
- 1.5Artificial Intelligence vs Machine Learning
- 1.6Artificial Intelligence vs Data Science
- 1.7Real-World Applications of AI
- 1.8AI Industry and Career Opportunities
- 1.9Understanding Intelligent Systems
- 1.10Setting Up the AI Learning Environment
- Python for Artificial Intelligence10
- Mathematics and Statistics for AI10
- Data Preparation for AI10
- Machine Learning Fundamentals10
- 5.1Introduction to Machine Learning
- 5.2Types of Machine Learning
- 5.3Supervised Learning
- 5.4Unsupervised Learning
- 5.5Reinforcement Learning Overview
- 5.6Machine Learning Workflow
- 5.7Training and Testing Data
- 5.8Overfitting and Underfitting
- 5.9Introduction to Scikit-learn
- 5.10Machine Learning Fundamentals Project
- Supervised Learning Algorithms10
- Unsupervised Learning Algorithms10
- Deep Learning Fundamentals10
- Advanced Deep Learning10
- Natural Language Processing10
- Computer Vision10
- Generative AI Fundamentals10
- 12.1Introduction to Generative AI
- 12.2Generative AI vs Traditional AI
- 12.3Understanding Large Language Models
- 12.4Introduction to Transformers
- 12.5Prompt Engineering Fundamentals
- 12.6AI Content Generation
- 12.7AI Image Generation Concepts
- 12.8AI-Powered Applications
- 12.9Responsible Generative AI
- 12.10Generative AI Mini Project
- AI Model Deployment10
- AI Ethics and Responsible AI10
- AI Live Projects and Capstone10
- 15.1AI-Based Prediction Project
- 15.2Customer Churn Prediction
- 15.3Image Classification Project
- 15.4Sentiment Analysis Project
- 15.5NLP Chatbot Project
- 15.6Computer Vision Application
- 15.7Generative AI Application
- 15.8AI Model Deployment Project
- 15.9End-to-End Artificial Intelligence Project
- 15.10Final Artificial Intelligence Capstone Project
