🎓 Enroll now & get 20% off — Limited time offer!
call +91 9391993605 mail [email protected]
Home
All Courses Python Training
About Us Contact Us Enroll Now →

Machine Learning Training Program

Go from statistical foundations to deployable ML models. Master regression, classification, clustering and MLOps through real-world projects across finance, healthcare, retail and telecom.

Course Highlights

What You'll Master

school

Strong ML Foundations

Build core intuition in statistics, linear algebra and the ML lifecycle before touching a single algorithm.

insights

Regression & Classification

Master 10+ supervised learning algorithms with rigorous evaluation metrics.

scatter_plot

Clustering & Unsupervised Learning

Apply K-Means, DBSCAN and PCA to uncover hidden patterns in unlabeled data.

rocket_launch

Real Industry Projects & MLOps

Ship models with Flask/FastAPI and learn the fundamentals of MLOps and monitoring.

Curriculum

Detailed Modules

  • Overview of Artificial Intelligence, Machine Learning and Deep Learning
  • Types of Machine Learning: Supervised, Unsupervised, Reinforcement Learning
  • Machine Learning lifecycle in industry
  • Real-world applications across finance, healthcare, retail and telecom
  • Tools and ecosystem overview (Python, Jupyter Notebook, Scikit-learn)
  • Linear Algebra fundamentals (vectors, matrices, matrix operations)
  • Basic Probability concepts
  • Descriptive Statistics (mean, variance, standard deviation)
  • Cost functions and loss functions
  • Gradient Descent (concept and optimization intuition)
  • Bias-Variance Tradeoff
  • Data collection and dataset understanding
  • Data cleaning techniques and handling missing values
  • Encoding categorical variables
  • Feature scaling (normalization and standardization)
  • Feature engineering fundamentals
  • Train-test split, cross-validation and Exploratory Data Analysis (EDA)
Algorithms Covered
  • Simple & Multiple Linear Regression
  • Polynomial Regression
  • Regularization Techniques (Ridge and Lasso)
Model Evaluation Metrics
  • MAE, MSE, RMSE
  • R-squared Score
Regression Projects
  • House Price Prediction (Real Estate Analytics)
  • Sales Forecasting System (Retail & E-commerce)
  • Salary Prediction Model (HR Analytics)
  • Energy Consumption Forecasting (Energy & Utilities)
Algorithms Covered
  • Logistic Regression, KNN, Naive Bayes
  • Decision Trees, Random Forest, SVM
Evaluation Metrics
  • Confusion Matrix, Accuracy, Precision, Recall
  • F1 Score, ROC-AUC
Classification Projects
  • Loan Approval Prediction (Financial Services)
  • Customer Churn Prediction (Telecom & SaaS)
  • Fraud Detection System (Banking & FinTech)
  • Email Spam Detection
  • Disease Risk Prediction (Healthcare Analytics)
Algorithms Covered
  • K-Means Clustering, Hierarchical Clustering, DBSCAN
  • Principal Component Analysis (PCA) for dimensionality reduction
Clustering Projects
  • Customer Segmentation (Marketing Analytics)
  • Market Basket Analysis (Retail Analytics)
  • Fraud Pattern Clustering (Cybersecurity)
  • Social Media User Segmentation (Digital Marketing)
  • Overfitting and underfitting
  • Cross-validation techniques
  • Hyperparameter tuning: Grid Search and Random Search
  • Model comparison strategies
  • Model serialization using Pickle and Joblib
  • Building REST APIs using Flask or FastAPI
  • Basic deployment concepts and introduction to MLOps
  • Model monitoring fundamentals
  • Problem statement definition and dataset acquisition
  • Exploratory Data Analysis and model development
  • Hyperparameter tuning and business interpretation of results
  • Basic deployment, final presentation and documentation
  • Apply regression, classification and clustering techniques to real datasets
  • Evaluate and optimize Machine Learning models
  • Solve practical business problems using data-driven approaches
  • Build a professional project portfolio and demonstrate readiness for entry-level industry roles
Tools Covered

Tools You'll Master

code Python dataset Jupyter Notebook model_training Scikit-learn table_chart Pandas & NumPy api Flask / FastAPI merge Git

Ready to Become a Data Pro?

Join our next cohort and gain the skills companies are looking for. Limited seats available.

Enroll Now Talk to an Expert