What You'll Learn

Python for ML

NumPy, Pandas, Matplotlib, Scikit-learn

Machine Learning

Supervised, Unsupervised, Algorithms

Deep Learning

Neural Networks, TensorFlow, Keras

NLP & MLOps

Natural Language Processing, Model deployment

Complete Syllabus

Python Basics: Variables, Data Types, Control Flow
Functions, Lambda, List Comprehensions
Object-Oriented Programming in Python
NumPy: Arrays, Vectorized Operations, Broadcasting
Pandas: DataFrames, Series, Data Cleaning
Working with CSV, JSON, and SQL Data Sources

Matplotlib & Seaborn for Data Visualization
Plotly for Interactive Charts
Descriptive Statistics: Mean, Median, Variance, Std Dev
Probability Distributions: Normal, Binomial, Poisson
Hypothesis Testing & p-values
Correlation and Covariance Analysis

Supervised Learning: Linear & Logistic Regression
Decision Trees & Random Forests
Support Vector Machines (SVM)
K-Nearest Neighbors (KNN)
Unsupervised Learning: K-Means Clustering
PCA for Dimensionality Reduction
Model Evaluation: Accuracy, Precision, Recall, F1-Score
Train/Test Split, Cross-Validation, Overfitting

Neural Network Fundamentals: Perceptrons, Activation Functions
Building Neural Networks with TensorFlow & Keras
PyTorch Basics: Tensors, Autograd, Model Training
Convolutional Neural Networks (CNN) for Image Classification
Recurrent Neural Networks (RNN) & LSTM
Transfer Learning with Pre-trained Models

Natural Language Processing: Tokenization, Stemming, Lemmatization
Text Classification & Sentiment Analysis
Word Embeddings: Word2Vec, GloVe
Transformer Architecture & Attention Mechanism
Large Language Models (LLM) Fundamentals
Prompt Engineering Techniques
Building AI Applications with OpenAI / Hugging Face APIs

Model Deployment with Flask / FastAPI
Model Versioning & Registry (MLflow)
Containerizing ML Models with Docker
Monitoring Model Performance in Production
Capstone Project: End-to-End ML Pipeline
Resume Building & Interview Preparation

Projects You'll Build

Predictive Analytics

Build ML models for predictions

Scikit-learn Python

Image Classification

Deep learning for image recognition

TensorFlow CNN

NLP Chatbot

Build intelligent chatbot

NLP Transformers

After Completing This Course You Will Be Able To

Build ML Models

Design, train, and evaluate machine learning models using Python, Scikit-learn, TensorFlow, and PyTorch

Implement Deep Learning

Build and deploy neural networks for image classification, NLP, and sequence prediction tasks

Deploy with MLOps

Containerize and deploy ML models to production with monitoring and versioning

Work with NLP & LLMs

Build NLP applications, work with transformers, and use prompt engineering effectively

Analyze Data

Clean, visualize, and extract insights from large datasets using Pandas and NumPy

Crack AI/ML Interviews

Prepare for technical interviews with real interview questions and mock interviews

Meet Your Instructor

Jagdish Kumawat

Founder & Director | 15+ Years Experience

Jagdish is the Founder & Director of MindverseAI with over 15 years of industry experience. He oversees the AI & Machine Learning program curriculum, ensuring it aligns with current industry practices and delivers practical, project-based learning.

Python TensorFlow Machine Learning Deep Learning NLP

Meet Our Full Team

Course Fee