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chakradbi

Machine Learning & MLOps Mastery

Master end-to-end machine learning — from core algorithms to real-world deployment. Build hands-on experience in data preprocessing, advanced ML models, and MLOps tools like MLflow, DVC, and Docker. Gain practical skills with real case studies, project work, and one-on-one interview-style evaluations. Ideal for aspiring data scientists, ML engineers, and AI practitioners.

Intermediate
12 -15 Weeks
Prerequisites

Python Programming

Basic statistics and data handling

EDA knowledge

Cloud & ETL Concepts

Learning Objectives :

Understand ML problem-solving lifecycle

Python Programming

Train, tune, and evaluate models effectively

Apply MLOps for reproducibility and collaboration

 Master the Tools That Matter

Master the platforms that drive today’s data-powered world and tomorrow’s tech innovations.

Program Curriculum

Introduction to ​ Machine Learning

What is Machine Learning?

Types of ML (Supervised, Unsupervised, Reinforcement)

ML lifecycle: Data Model Deployment

Bias-Variance Tradeoff

Model Evaluation Metrics (Accuracy, Precision, Recall, AUC)

Core Machine Learning Algorithms

Linear & Logistic Regression

Decision Trees & Random Forest

K-Nearest Neighbors (KNN)

Naive Bayes

Support Vector Machines (SVM)

Data Prep & Feature Engineering

Data Cleaning & Missing Values

Feature Scaling & Transformation

Feature Selection & Dimensionality Reduction

Outlier Detection Techniques

Advanced ML Techniques

Gradient Boosting (XGBoost, LightGBM, CatBoost)

Hyperparameter Tuning (Grid Search, Random Search, Optuna)

Cross-Validation Techniques

Model Explainability (SHAP, LIME)

Model Stacking and Ensemble Methods

ML Operations  and  Deployment

Version Control with DVC

Experiment Tracking with MLflow

Creating APIs using FastAPI

Model Packaging with Docker

CI/CD with GitHub Actions

Cloud Deployment (AWS Sagemaker or Streamlit + EC2)

Introduction ​ to Deep Learning

Basics of Neural Networks

Overview of CNN & RNN

Use cases in NLP & Vision

Hands-on with TensorFlow or PyTorch

The Chakra Edge: Learn Smarter, Rise Faster

Experience personalized learning with expert-led small batches, hands-on projects, and continuous interview prep. Track your growth with our intelligent LMS—designed to sharpen your skills at every chapter. This is not just a course, it's your launchpad to a high-impact data science career.

Small Batch Size - Personalized Attention

Get individual attention with 4–5 learners per group—collaborative, focused, and personal.

Portfolio-Ready Capstone Project for Real Impact

Turn theory into action by solving real-world challenges and building a standout portfolio.

Ace Interview - From Concept to Confidence

Get individual attention with 4–5 learners per group—collaborative, focused, and personal.

LMS - Intelligent Tracking, Smarter Learning

Get individual attention with 4–5 learners per group—collaborative, focused, and personal.