EMPIRES COMPUTER
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Advanced IT
Official Course Syllabus & Career Roadmap
Artificial Intelligence (AI)
Artificial Intelligence & Machine Learning foundations, Deep Learning, Natural Language Processing, LLMs, and Generative AI.
Course Overview
Artificial Intelligence & Machine Learning foundations, Deep Learning, Natural Language Processing, LLMs, and Generative AI.
Target Audience & Who Should Join
- Students & IT Professionals wanting an AI competitive edge
- Designers, Marketers & Content Creators leveraging generative AI
- Entrepreneurs building automated business workflows
Detailed Course Syllabus Modules
Module 1: Python for AI & Data Foundations
- Python Essentials for AI: Object-Oriented Programming, Lambda Functions & List Comprehensions
- Mathematical Foundations for AI: Linear Algebra, Statistics, Probability & Calculus Concepts
- Data Handling & Manipulation with NumPy Arrays and Pandas DataFrames
- Exploratory Data Analysis (EDA) & Data Visualization with Matplotlib & Seaborn
Module 2: Machine Learning Algorithms & Scikit-Learn
- Supervised Learning: Linear Regression, Logistic Regression, Decision Trees & Random Forests
- Support Vector Machines (SVM), K-Nearest Neighbors (KNN) & Naive Bayes Classifiers
- Unsupervised Learning: K-Means Clustering, Hierarchical Clustering & Principal Component Analysis (PCA)
- Model Evaluation & Optimization: Cross-Validation, Confusion Matrix, Precision-Recall, ROC-AUC & Hyperparameter Tuning
Module 3: Deep Learning, Neural Networks & Computer Vision
- Neural Network Architecture: Perceptrons, Activation Functions (ReLU, Softmax), Forward & Backpropagation
- Deep Learning Frameworks: Introduction to PyTorch / TensorFlow & Keras
- Convolutional Neural Networks (CNNs) for Image Recognition & Object Detection
- Recurrent Neural Networks (RNNs) & LSTMs for Sequential Data and Time Series Forecasting
Module 4: Generative AI, Large Language Models (LLMs) & Capstone Projects
- Generative AI & Transformer Architecture (Attention Mechanisms, GPT, BERT)
- Advanced Prompt Engineering Techniques (Few-Shot, Chain-of-Thought, System Prompts)
- Integrating OpenAI APIs, Claude APIs & Open-Source LLMs (Llama 3, Mistral)
- Building Custom AI Chatbots with Retrieval-Augmented Generation (RAG) & Vector Databases
- AI Image & Media Generation: Midjourney, Stable Diffusion & DALL-E Workflows
- Capstone Real-World AI Project: End-to-End AI Web Application Deployment with Streamlit
Practical Design Examples & Live Projects Included
🤖 Custom RAG AI Chatbot
Building a conversational AI assistant connected to custom PDF documents using LangChain & vector databases.
🧠 Image Classification & Object Detection
Training Convolutional Neural Networks (CNN) with PyTorch/TensorFlow on custom visual datasets.
📊 Predictive Machine Learning Models
Deploying regression and classification algorithms for customer churn and price prediction.
⚡ Full-Stack AI App Deployment
Building and deploying an interactive AI web application on cloud servers using Streamlit & FastAPI.
Career Opportunities & Job Profiles
AI Prompt Engineer
Generative AI Specialist
Automation Consultant
AI Workflow Specialist
Empires Computer Rajkot - 100% Practical Training & Placement
Generated Date: 05 Nov 2026