Why Learn Artificial Intelligence?
Artificial Intelligence (AI) is transforming industries worldwide—from healthcare and finance to retail and autonomous systems. With AI-driven automation, Generative AI applications, and advanced analytics, organizations are seeking skilled professionals who can design, develop, and deploy intelligent solutions. Our AI Training Program equips you with industry-relevant skills, hands-on experience, and the latest tools to make you job-ready for high-demand AI roles.
Who Should Enroll?
- IT professionals looking to upskill in AI and ML
- Data analysts and engineers aiming for AI-driven roles
- Students and graduates aspiring for careers in AI
- Business professionals exploring AI applications in their domain
Key Features of Our AI Training
- Offline & Online Training Options
- Hands-on Projects & Capstone
- Placement Assistance & Career Support
- Industry-Recognized Certification
- Expert Mentorship from AI Practitioners
Module 1: Foundations of AI
- Introduction to AI: History, Applications, and Trends
- AI vs ML vs Deep Learning
- Overview of AI in Business and Industry
Module 2: Mathematics & Programming for AI
- Python for AI: NumPy, Pandas, Matplotlib
- Mathematics for AI:
- Linear Algebra (Vectors, Matrices, Eigenvalues)
- Probability & Statistics (Distributions, Hypothesis Testing)
- Calculus for Optimization
Module 3: Machine Learning
- Supervised Learning: Linear & Logistic Regression, Decision Trees
- Unsupervised Learning: Clustering (K-Means), Dimensionality Reduction (PCA)
- Ensemble Methods: Random Forest, Gradient Boosting
- Model Evaluation & Cross-Validation
Module 4: Deep Learning
- Neural Networks: Architecture & Backpropagation
- Convolutional Neural Networks (CNNs) for Computer Vision
- Recurrent Neural Networks (RNNs) & LSTMs for Sequential Data
- Transfer Learning & Pre-trained Models
Module 5: Generative AI & Advanced Topics
- Generative AI Foundations: GANs, Variational Autoencoders
- Large Language Models (LLMs): GPT, BERT, and Transformer Architectures
- Prompt Engineering & Retrieval-Augmented Generation (RAG)
- Agentic AI and Autonomous Systems
- AI for Text, Image, and Video Generation
Module 6: Natural Language Processing (NLP)
- Text Preprocessing & Feature Engineering
- Sentiment Analysis & Named Entity Recognition
- Advanced NLP with Transformers & LLMs
Module 7: Computer Vision
- Image Processing & Feature Extraction
- Object Detection (YOLO, Faster R-CNN)
- Image Segmentation & Augmentation
Module 8: AI in Business & Deployment
- AI in Cloud (AWS, Azure, GCP)
- MLOps & Model Deployment
- AI for Recommendation Systems
- AI in Finance, Healthcare, and Retail
Module 9: Ethics & Responsible AI
- AI Bias & Fairness
- Explainable AI (XAI)
- Data Privacy & Compliance
Capstone Project
- Real-world AI project in Healthcare, Finance, or Retail
- Build an AI-powered application using ML, DL, and Generative AI
Tools & Frameworks Covered
- Programming: Python
- Libraries: TensorFlow, PyTorch, Scikit-learn, OpenCV
- Generative AI Tools: OpenAI API, Hugging Face, LangChain
- Visualization: Matplotlib, Seaborn, Power BI
- Cloud Platforms: AWS, Azure, GCP
Career – Interview Preparation
- AI Engineer & Data Scientist Role
- GenAI Engineer