Advanced ML Techniques

Gain expertise in hyperparameter tuning, model optimization, and evaluation metrics.

⏱️ Duration:14 hrs
💰 Fee:₹ 2999 + Taxes
🎯Weekend batch

View our curriculum

The entire program leads to mastery in the field and is intended to give future practitioners a complete curriculum.

Module 1

Model Evaluation & Validation

🎓

Train-Test Split Review

ML Practitioner

🌟

Cross-Validation Techniques

ML Practitioner

K-Fold, Stratified K-Fold

📊

Model Selection & Validation

ML Practitioner

Grid Search & Random Search, Hyperparameter tuning with GridSearchCV

Module 2

Data Preprocessing

🧹

Data Cleaning

ML Practitioner

Handling missing values (Imputation Techniques), Dealing with outliers

⚙️

Feature Engineering

ML Practitioner

One-Hot Encoding, Feature Scaling (Standardization & Normalization)

✂️

Splitting Data

ML Practitioner

Train-test split, K-Fold Cross-Validation

Module 3

Feature Engineering & Model Optimization

📈

Linear Regression

ML Practitioner

Stationarity & trend analysis

🎯

ARIMA and SARIMA models

ML Practitioner

📊

Time series forecasting

ML Practitioner

Module 4

Ensemble Methods

🌲

Bagging & Boosting

ML Practitioner

Random Forest, XGBoost & AdaBoost

🔗

Model Stacking

ML Practitioner

Combining multiple models for improved accuracy

Module 5

Introduction to Reinforcement Learning (RL)

🎲

Markov Decision Processes (MDPs)

ML Practitioner

Fundamentals of MDPs

🤖

Q-Learning & Deep Q-Networks (DQN)

ML Practitioner

Value-based RL methods

📈

Policy Gradient Methods

ML Practitioner

Optimizing policies directly

Module 6

Bayesian Machine Learning

🔍

Bayesian Networks & Probabilistic Programming

ML Practitioner

Understanding Bayesian methods

⚠️

Uncertainty Estimation in ML Models

ML Practitioner

Handling uncertainty in predictions

ML Explorer Projects:

Sharpen Your Skills with 4+ Battles

Master AI by working on 4+ real-world projects—building, innovating, and solving challenges to prepare for the fast-moving industry.

ML Practitioner

AutoML Tuning

Automating model selection and hyperparameter tuning using AutoML frameworks

ML Practitioner

Stock Forecasting

Predicting stock prices using time-series models like ARIMA and LSTM.

ML Practitioner

Fake News Detection

Classifying news articles as fake or real using ensemble learning techniques

ML Practitioner

Car Simulation

Training an autonomous vehicle to navigate using Reinforcement Learning.

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