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Batch
Date: June 27th & 28th @5:00AM
Faculty: Khan Trainer (10+ Yrs of Exp,.. & Real time Expert)
Duration: 20 to 25 Weekends Batch (Sat: 3 Hours, Sun: 3 Hours)
Venue
:
DURGA SOFTWARE SOLUTIONS,
Flat No : 202,
2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038
Ph.No: +91 - 8885252627, 9246212143, 80 96 96 96 96
Syllabus:
Job-Ready Full Stack AI Engineering Program
(Data Science, GenAI, MLOps & Cloud)
with End-to-End Project Development & Production Deployment
Topics:
Python Programming Language:
- Introduction to Python
- Importance of Python
- Software Installation
- IDE Setup
- Visual Studio Code
- Jupyter Notebook
- Anaconda
- Features of Python
- Characteristics
- Quotations
- Line Indentation
- Reserved Words
- Variables
- Data Types
- Operators
- Different Types of Operators
- Python Collections (List, Tuple, Set, Dictionary)
- Functions
- Lambda Functions
- List Comprehensions
- Iterators
- Generators
- Decorators
- Exception Handling
- File Handling
- Modules
- Packages
- Pickling
- UnPickling
- OOPs Concepts
- Constructors
- Access Modifiers
- Regular Expression
- Multithreading Use Cases
- Examples & Scenarios
Project - 1:
Data Science
- Introduction to Data Science
- Importance of Data Science
- Why Data Science
- Data Science Project Lifecycle
- Installation of Libraries
- NumPy
- Pandas
- SciPy
- Data Wrangling
- Data Preprocessing
- Feature Engineering
- Data Analysis with Use Cases
- Examples & Scenarios
Project - 2:
Data Visualization
- Introduction to Data Visualization
- Installation Libraries
- Matplotlib
- Seaborn
- Exploratory Data Analysis (EDA)
- Graphs including Histograms
- Box Plots
- Bar Charts
- Pie Charts
- Scatter Plots and Heat Maps
- Examples & Scenarios
Project - 3:
Statistics and Probability
- Introduction to Statistics
- Sample, Population
- Data Types: Continuous and Discrete
- Central Tendency Mean
- Median
- Mode
- Variance
- Standard Deviation
- IQR
- Probability
- Probability Distributions
- Normal Distribution
- Central Limit Theorem (CLT)
- Sampling Techniques
- Hypothesis Testing
- Confidence Intervals
- Correlation
- Covariance
- Skewness
- Kurtosis
- Examples
Project - 4:
Machine Learning
- Introduction to Machine Learning
- Types of Machine Learning
- Supervised Learning
- Unsupervised Learning
- ML Workflow
- Feature Engineering
- Train-Test Split
- Model Validation Techniques
- Cross Validation
- Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Metrics Accuracy
- Precision, Recall
- F1 Score
- ROC-AUC
- K-Nearest Neighbors (KNN)
- Naive Bayes
- Decision Tree
- Random Forest
- Data Transformation
- Underfitting
- Overfitting
- Bias-Variance Tradeoff
- Hyperparameter Tuning
- Regularization Techniques
- Boosting Methods
- Gradient Boosting
- XGBoost
- Ada Boost
- GridSearchCV
- RandomizedSearchCV
- Clustering
- K-Means
- Hierarchical Clustering
- DBSCAN
- PCA
- Pipeline Concepts
- Ensemble Techniques
- Recommendation Systems
- Time Series Analysis
- Use Cases
- Examples
- Scenarios
- Working on Case Study
Project - 5:
Deep Learning
- Introduction to Deep Learning
- TensorFlow
- Keras
- PyTorch
- Installation Setup
- Neural Networks
- Perceptron
- Back Propagation Method
- Multilayer Neural Networks
- Activation Functions
- Loss Functions
- Optimizers (SGD, Adam)
- Artificial Neural Networks (ANN)
- Classification using ANN
- Dropout
- Batch Normalization
- RNN
- LSTM Architecture
- Convolution
- Pooling
- CNN Architecture
- Image Classification
- Use Cases
- Examples
- Scenarios
- Working on Case Study
Project - 6:
NLP (Natural Language Processing)
- Introduction to NLP
- NLTK & spaCy Installation
- NLP Lifecycle
- Text Cleaning
- Regular Expressions
- Tokenization
- Stop Words
- Stemming
- Lemmatization
- POS Tagging
- Named Entity Recognition (NER)
- Bag of Words (BoW)
- TF-IDF
- Word2Vec
- FastText
- GloVe
- Text Classification Concepts
- Word Embedding
- Pre-trained Word Embeddings
- Skip Gram
- CBOW
- Language Modeling N-gram Models
- Real-Time Applications
Project - 7:
Prompt Engineering
- Introduction to Prompt Engineering
- Prompt Design
- Prompt Templates
- Zero-Shot
- One-Shot
- Few-Shot & Chain-of-Thought Prompting
- Role-Based Prompting
- Structured Output & JSON Prompting
- Prompt Chaining
- Temperature
- Top-K & Top-P Sampling
- Prompt Optimization
- Prompt Evaluation
- Best Practices
- Real-Time Use Cases & Scenarios
Project - 8:
Generative AI
- Introduction to Generative AI
- Foundation Models
- Large Language Models (LLMs) Transformer Architecture
- Encoder Architecture
- Decoder Architecture
- Attention Mechanism
- Self-Attention
- Tokenization
- Context Window
- Embeddings
- Semantic Search
- Vector Databases
- FAISS
- ChromaDB
- Pinecone
- Weaviate
- Retrieval-Augmented Generation (RAG)
- Hybrid Search
- Re-ranking
- LangChain
- OpenAI API
- Gemini API
- Hugging Face Inference API
- MCP (Model Context Protocol)
- Building End-to-End RAG Applications
- Real-Time Use Cases
- Examples & Scenarios
Project - 9:
AI Agents
- Introduction to AI Agents
- LangChain Setup
- Agent Components
- Tool Calling
- Function Calling
- Agent Tools
- Memory Types (Short-Term & Long-Term)
- Planning & Execution
- ReAct Framework
- Single-Agent Systems
- Agent Workflows
- Building AI Agents using LangChain
- MCP Integration
- Multi-Tool Agents
- Real-Time Agent Applications
Project - 10:
Agentic AI
- Introduction to Agentic AI
- CrewAI Installation
- LangGraph Installation
- AutoGen Installation
- Autonomous Agents
- Reflection
- Multi-Step Reasoning
- Task Planning
- Task Decomposition
- Human-in-the-Loop
- Multi-Agent Systems
- Agent Collaboration
- Agent Evaluation Concepts
- Agentic AI Applications
- Use Cases, Examples
- Working on a Case Study
Project - 11:
DevOps
- Introduction to DevOps
- SDLC
- Agile Methodology
- Git Installation
- Git Fundamentals
- GitHub Account Setup
- GitHub Repositories
- Git Workflow
- Branching & Merging
- Merge Conflict Resolution
- gitignore
- Pull Requests
- CI/CD Concepts
- Continuous Integration
- Continuous Delivery
- Continuous
- Deployment
- Jenkins Installation
- Jenkins Architecture
- Jenkins Pipelines
- Jenkinsfile
- Build Automation
Project - 12:
MLOps
- Introduction to MLOps
- MLflow Installation
- Machine Learning Lifecycle
- Data Versioning
- Model Versioning
- Experiment Tracking
- MLflow
- Model Registry Concepts
- Model Deployment Concepts
- Model Monitoring
- Data Drift
- Model Drift
- Retraining Strategies
- Production ML Pipelines
- MLOps
Project - 13:
Docker
- Introduction to Containerization
- Docker Installation
- Docker Fundamentals
- Docker Architecture
- Docker Images
- Docker Containers
- Dockerfile
- Docker Commands
- Docker Volumes
- Docker Networking
- Docker Compose
- Docker Hub
Project - 14:
Kubernetes
- Introduction to Kubernetes
- Minikube Installation
- Kubernetes Architecture
- Pods
- ReplicaSets
- Deployments
- Services
- ConfigMaps
- Secrets
- Namespaces
- Scaling
- Rolling Updates
- Container Orchestration
Project - 15:
GCP (Google Cloud Platform)
- Introduction to Cloud Computing
- Cloud Service Models (IaaS, PaaS, SaaS)
- GCP Overview
- GCP Account Setup
- IAM
- Billing Management
- Cloud Storage
- Compute Engine
- BigQuery
- Vertex AI
- Vertex AI Workbench
- Vertex AI Pipelines
- Vertex AI Model Deployment
- Gemini on Vertex AI
- Cloud Run
- Cloud Functions
Project - 16:
Cloud & Deployment
- Introduction to Deployment
- Streamlit Installation
- FastAPI Installation
- REST API Concepts
- API Testing using Postman
- ML Model Deployment
- Deep Learning Model Deployment
- RAG Application Deployment
- AI Agent Deployment
- Enterprise Architecture
- End-to-End Capstone Project Development & Production Deployment
Project - 17:
Free Value-Added Classes
Project – 18, Project - 19:
Final Project: Project – 20
Resume:
- Resume Building
- ATS-Friendly Resume Preparation
- Career Guidance
GitHub Account:
- GitHub Account Creation
- Repository Management
- Project Uploads
- Portfolio Development
- Code Showcase
Interview Preparation:
- Technical Interview Preparation
- Mock Interviews
- Resume Review
- LinkedIn Profile Optimization
- Job Search Strategy
Certificate of Completion will be awarded upon successful completion of the training program and project submissions
