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Offered by: VVR Technologies Duration: 8 Weeks (2 Months) Mode: Online / In-Person / Hybrid Level: Beginner to IntermediateMaster the essentials of Artificial Intelligence and Machine Learning in just 2 months. This hands-on program combines Python programming, Machine Learning algorithms, and Generative AI tools — including the latest Agentic AI and RL (Reinforcement Learning) — to help you build smart, real-world AI systems.
By the end, you’ll design and deploy your own Mini AI Project using Python and cloud-based AI platforms.
Learn Python, ML, and GenAI in one 2-month courseGain hands-on skills in Agentic AI and Reinforcement LearningBuild real-world projects every weekDeploy your own AI app onlineGet certified by VVR Technologies
Python basics: syntax, data types, loops, and functions Working with NumPy and Pandas for data processing Data cleaning and transformation Using Jupyter Notebook & Google Colab effectively Python, Jupyter, Google Colab Clean and analyze a sample dataset (e.g., sales or healthcare). Combine the power of Agentic AI, Generative AI, and Reinforcement Learning (RL) to
create intelligent systems that act, learn, and adapt for real-world use cases. Introduction to Artificial Intelligence (AI 2025 landscape) Agentic AI: how intelligent agents plan and act autonomously Generative AI: LLMs, text-to-image, and text-to-code generation Reinforcement Learning: agents learning from rewards and environment Integration of Agentic AI + Gen AI + RL in business and automation workflows Hands-on with ChatGPT, Gemini, and Hugging Face Transformers OpenAI API, Gemini, Hugging Face, LangChain, Python Create an AI Agent that uses a Generative AI model and learns user preferences using RL feedback loop. Industry insights on Agentic AI applications (e.g., autonomous customer support, adaptive recommendation systems). Exploratory Data Analysis (EDA) Correlation, distributions, and data storytelling Visualization with Matplotlib & Seaborn Intro to Power BI dashboards Pandas, Matplotlib, Seaborn, Power BI Build an interactive insights dashboard from real datasets. ML pipeline: data → model → evaluation Supervised vs Unsupervised learning Linear & Logistic Regression Decision Trees and Random Forests Model evaluation (accuracy, precision, recall) Scikit-learn, NumPy, Pandas Build a House Price Prediction or Customer Churn Model. Neural network basics & architecture Activation functions, backpropagation Intro to TensorFlow and Keras Image and text processing concepts TensorFlow, Keras Train a Handwritten Digit Recognizer (MNIST). Text generation and summarization Prompt engineering for ChatGPT, Claude, Gemini Building simple chatbots and text classifiers Intro to vector embeddings and retrieval-augmented generation (RAG). OpenAI API, Hugging Face, LangChain Create a ChatGPT-powered Q&A Assistant. Model saving (Pickle / Joblib) Building web apps with Streamlit Deploying models on Render, Hugging Face, or Google Cloud Intro to MLOps & Continuous Model Integration. Streamlit, Render, GitHub, AWS (Intro). Deploy your AI model as a live app. AI Chatbot with Agentic Workflow Sales Forecasting using ML Sentiment Analyzer (Text + GenAI) AI Resume Screener / Interview Bot Working end-to-end project. Deployed model link. GitHub repo. Presentation deck.
Prompt Engineering Masterclass (ChatGPT, Gemini, Copilot) Agentic AI Frameworks (LangChain, CrewAI, LlamaIndex) AI Ethics & Responsible AI Career Prep: Portfolio Building & AI Interview ReadinessAfter completion, learners can apply for
AI / ML Engineer (Junior) Data Analyst (AI-integrated) AI Solutions Developer Generative AI Specialist Python Developer (AI Automation)| Category | Tools / Technologies |
|---|---|
| Programming | Python, Jupyter, Colab |
| Data Handling | Pandas, NumPy |
| Visualization | Matplotlib, Seaborn, Power BI |
| ML Frameworks | Scikit-learn, TensorFlow, Keras |
| AI & GenAI Tools | ChatGPT, Gemini, Hugging Face, LangChain |
| Deployment | Streamlit, Render, AWS |
| Agentic & RL | OpenAI API, Gymnasium (Intro), LangChain |
Python programming for AI & ML Data cleaning, visualization, and EDA Core ML algorithms (Regression, Classification, Clustering) Generative AI, Agentic AI, and RL fundamentals Deep learning basics using TensorFlow & Keras Deploying AI models using Streamlit or Hugging Face Cloud and automation tools for real-world AI appsMaster the art of front-end, back-end, databases, APIs, and deployment in one comprehensive program. Learn how to design, build, and scale web applications end-to-end.
Master the tools and frameworks that power modern AI — from prompt engineering to building generative applications.
Develop end-to-end data science expertise — from data wrangling to AI-powered predictions — using real-world business datasets.
Learn how to drive growth, brand visibility, and online engagement through data-driven digital marketing strategies.
Strengthen your expertise in protecting digital systems and networks. Learn modern cyber security tools, threat-analysis techniques.