Machine Learning Training Institute in Dilsukhnagar Hyderabad

Welcome to SR Digital Academy – SAP, Data Science & AI Training Institute, a leading Machine Learning training institute in Dilsukhnagar, Hyderabad. Our Machine Learning Course is designed to help students, graduates, IT professionals, and aspiring data scientists master the concepts of Machine Learning and build intelligent predictive models using real-world datasets.

Machine Learning is one of the most in-demand technologies in today’s digital world and forms the foundation of Artificial Intelligence. This course provides comprehensive training in Python, Data Analysis, Statistics, Supervised Learning, Unsupervised Learning, Deep Learning, Model Deployment, and Machine Learning Project Development.

At SR Digital Academy, learners gain hands-on experience through live projects, industry case studies, assignments, and practical exercises that prepare them for real-world Machine Learning roles and career opportunities.

Why Choose SR Digital Academy for Machine Learning Training?

  • Industry-oriented curriculum

  • Practical learning with real-time projects

  • Expert trainers with industry experience

  • Hands-on Machine Learning model development

  • Interview preparation and placement assistance

  • Flexible classroom and online training

  • Certification upon course completion

  • Career guidance and resume building support

Machine Learning Course Content

Module 1: Introduction to Machine Learning

  • What is Machine Learning?

  • Applications of Machine Learning

  • Types of Machine Learning

  • Machine Learning Workflow

  • Industry Use Cases

  • Career Opportunities in Machine Learning

Module 2: Python Programming for Machine Learning

  • Python Basics

  • Variables and Data Types

  • Conditional Statements

  • Loops and Functions

  • Object-Oriented Programming

  • File Handling

  • Python Libraries Overview

Module 3: Mathematics and Statistics for Machine Learning

  • Linear Algebra Fundamentals

  • Matrices and Vectors

  • Probability Concepts

  • Descriptive Statistics

  • Inferential Statistics

  • Hypothesis Testing

  • Correlation and Covariance

Module 4: Data Analysis and Data Preprocessing

  • Data Collection Techniques

  • Data Cleaning

  • Handling Missing Values

  • Outlier Detection

  • Feature Engineering

  • Feature Scaling

  • Data Transformation

  • Exploratory Data Analysis (EDA)

Module 5: Python Libraries for Machine Learning

  • NumPy

  • Pandas

  • Matplotlib

  • Seaborn

  • Scikit-Learn

  • Jupyter Notebook

  • Google Colab

Module 6: Supervised Learning Algorithms

  • Linear Regression

  • Multiple Linear Regression

  • Logistic Regression

  • Decision Trees

  • Random Forest

  • K-Nearest Neighbors (KNN)

  • Support Vector Machines (SVM)

  • Naive Bayes

Module 7: Model Evaluation Techniques

  • Train-Test Split

  • Cross Validation

  • Accuracy

  • Precision

  • Recall

  • F1 Score

  • ROC Curve

  • Confusion Matrix

Module 8: Unsupervised Learning Algorithms

  • Clustering Concepts

  • K-Means Clustering

  • Hierarchical Clustering

  • DBSCAN

  • Market Basket Analysis

  • Association Rules

Module 9: Dimensionality Reduction

  • Principal Component Analysis (PCA)

  • Feature Selection Techniques

  • Feature Extraction

  • Data Visualization Techniques

Module 10: Ensemble Learning

  • Bagging Techniques

  • Boosting Techniques

  • Random Forest

  • AdaBoost

  • Gradient Boosting

  • XGBoost Introduction

Module 11: Introduction to Deep Learning

  • Artificial Neural Networks

  • Activation Functions

  • Forward Propagation

  • Backpropagation

  • TensorFlow Basics

  • Keras Framework

Module 12: Machine Learning Model Deployment

  • Model Serialization

  • Flask Framework

  • Streamlit Applications

  • API Integration

  • Deployment Best Practices

  • Cloud Deployment Overview

Module 13: Real-Time Machine Learning Projects

Beginner Projects

  • Student Performance Prediction

  • House Price Prediction

  • Sales Prediction

Intermediate Projects

  • Customer Churn Prediction

  • Loan Approval Prediction

  • Employee Attrition Analysis

Advanced Projects

  • Fraud Detection System

  • Recommendation Engine

  • Predictive Analytics Dashboard

  • Machine Learning Business Intelligence Solution

Module 14: Industry Case Studies

  • Banking Analytics

  • Healthcare Analytics

  • Retail Analytics

  • Marketing Analytics

  • Financial Forecasting

  • HR Analytics

Module 15: Career Preparation

  • Resume Building

  • GitHub Portfolio Creation

  • LinkedIn Optimization

  • Interview Questions

  • Mock Interviews

  • Placement Assistance

Tools Covered

  • Python

  • NumPy

  • Pandas

  • Matplotlib

  • Seaborn

  • Scikit-Learn

  • Jupyter Notebook

  • Google Colab

  • TensorFlow

  • Keras

  • Streamlit

  • Flask

  • Git & GitHub

Course Duration

  • Fast Track Program – 2 Months

  • Regular Program – 3 Months

  • Advanced Program – 4 Months

Career Opportunities After Machine Learning Training

  • Machine Learning Engineer

  • Data Scientist

  • AI Engineer

  • Data Analyst

  • Business Intelligence Analyst

  • Predictive Analytics Specialist

  • Research Analyst

  • AI & Machine Learning Consultant

Certification

Upon successful completion of the Machine Learning Course, students will receive a Machine Learning Certification from SR Digital Academy along with project experience certification and placement assistance support.

Join the best Machine Learning Course Training in Dilsukhnagar Hyderabad at SR Digital Academy – SAP, Data Science & AI Training Institute and build a successful career in Artificial Intelligence, Data Science, and Machine Learning.