Best Applied Artificial Intelligence & Machine Learning in Surat
Go beyond theory with Surat’s only hands-on AI/ML course.
Learn to build real predictive models, integrate LLMs, and develop your own AI agents to solve complex industry problems.
Duration: 10 Months
Course Curriculum
Python for Data Science & AI Foundations
- Setting up the AI development environment (Jupyter Notebooks, Google Colab, Anaconda).
- Python crash course for AI: Data structures, functions, and object-oriented programming.
- Mastering NumPy for high-performance numerical computing and matrix operations.
- Data manipulation and cleaning with Pandas: Handling missing data, merging, and filtering.
- Data visualization essentials using Matplotlib and Seaborn to understand data distributions.
Exploratory Data Analysis (EDA) & Feature Engineering
- Techniques for understanding structured vs. unstructured data.
- Identifying correlations, outliers, and statistical significance in datasets.
- Feature engineering: Encoding categorical variables, scaling, and normalization.
- Dimensionality reduction techniques (PCA) to optimize dataset performance.
- Splitting data into training, validation, and testing sets to prevent data leakage.
Applied Predictive Modeling (Machine Learning)
- Introduction to Scikit-Learn and the traditional Machine Learning pipeline.
- Supervised Learning (Regression): Predicting continuous values (Linear Regression, Ridge/Lasso).
- Supervised Learning (Classification): Predicting categories (Logistic Regression, SVMs, KNN).
- Model evaluation metrics: Accuracy, Precision, Recall, F1-Score, and the Confusion Matrix.
- Hyperparameter tuning using Grid Search and Random Search.
Advanced ML: Ensemble Methods & Unsupervised Learning
- Decision Trees and the power of ensemble learning.
- Building high-accuracy models with Random Forests and Gradient Boosting (XGBoost/LightGBM).
- Unsupervised Learning: Discovering hidden patterns using K-Means Clustering.
- Solving real industry problems: Customer churn prediction, price forecasting, and anomaly detection.
- Saving and loading trained models using Pickle and Joblib.
Deep Learning & Neural Network Foundations
- Understanding the shift from traditional ML to Deep Learning.
- Introduction to PyTorch or TensorFlow/Keras frameworks.
- The architecture of a Neural Network: Perceptrons, hidden layers, and activation functions (ReLU, Sigmoid).
- Forward propagation, backpropagation, and understanding loss functions.
- Building a basic Multi-Layer Perceptron (MLP) for complex classification tasks.
NLP & Vector Databases for Modern AI
- Introduction to Natural Language Processing (NLP) and text tokenization.
- Understanding word embeddings and semantic search.
- Generating vector embeddings using OpenAI and Hugging Face embedding models.
- Setting up and querying Vector Databases (e.g., Pinecone, ChromaDB, or Weaviate).
- Implementing highly accurate semantic search for large document structures.
Integrating Large Language Models (LLMs)
- Overview of the LLM landscape: OpenAI (GPT-4), Google (Gemini), and Open-Source (Llama 3).
- Obtaining API keys and securely integrating LLM APIs into Python applications.
- Advanced Prompt Engineering: Few-shot prompting, chain-of-thought, and system prompts.
- Controlling LLM output formatting (JSON parsing) for seamless application integration.
- Fine-tuning fundamentals: When to fine-tune vs. when to use prompt engineering.
Building AI Agents & RAG Applications
- Introduction to LangChain and LlamaIndex for orchestrating complex AI workflows.
- Building Retrieval-Augmented Generation (RAG) pipelines to let LLMs "chat" with your private data (PDFs, databases).
- Giving AI tools: Creating autonomous AI Agents that can search the web, execute code, or query SQL databases.
- Managing agent memory and conversational context over long sessions.
- Solving complex problems with multi-agent architectures.
Model Deployment & MLOps
- Transitioning from Jupyter Notebooks to production-ready Python scripts.
- Building interactive web interfaces for AI models instantly using Streamlit or Gradio.
- Wrapping predictive models and LLM agents into RESTful APIs using FastAPI.
- Containerizing the AI application and its dependencies using Docker.
- Deploying the AI API to cloud platforms (AWS, Render, or Hugging Face Spaces).
Industry Capstone Project & Career Placement
- Building a full-scale, portfolio-ready AI application (e.g., an automated customer support agent, a real estate price predictor, or an intelligent document analyzer).
- Best practices for version controlling data and models (Git/DVC).
- Preparing for technical data science and AI engineering interviews.
- Navigating Surat's evolving tech landscape and positioning yourself as a specialized AI developer.
Why Choose Extrabits for Applied Artificial Intelligence & Machine Learning Training?
At Extrabits Academy, we provide the best Applied Artificial Intelligence & Machine Learning course in Surat, offering more than just theory — we provide an opportunity to enhance your career with practical knowledge and live project experience.
Gain insights from professionals with years of real-world experience.
Work on live projects and build a portfolio that stands out.
Choose from weekend or weekday batches to suit your schedule.
Master core concepts and advanced techniques in modern technology.
Apply your skills to solve real business problems through case studies.
Earn a recognized certificate to boost your career opportunities.
Student Reviews (3)
Average Rating: 5/5 ★ from 3 students
May 6, 2026
★★★★★
"“I completed the Applied Artificial Intelligence & Machine Learning course at ExtraBits Academy and it was a great experience. The course explains complex AI and ML concepts in a very simple and practical way. Working on real datasets and models helped me understand how AI works in real-world..."
May 6, 2026
★★★★★
"“I joined ExtraBits Academy for Applied AI & ML and gained strong practical knowledge. The training focuses on real implementation instead of just theory, which makes learning effective. Building machine learning models step by step improved my understanding and confidence. One of the best places..."
May 6, 2026
★★★★★
"“I joined the AI and Machine Learning course at ExtraBits Academy, and it exceeded my expectations. The course simplifies complex topics like algorithms, model training, and evaluation using easy-to-understand explanations. The practical implementation of machine learning models helped me gain..."
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