Advanced Machine Learning course – Build AI Models Like the Experts
Advanced (ML & DL) Course in Telugu cutting-edge AI techniques. It covers neural networks, optimization, and real-world applications.
100% Live
Training
2 Years
Recordings
Free
Addon Sessions
Real Time
Projects
Machine Learning Course Boosts Your Job Prospects
Hiring Demand
ML & DL roles are among the top 5 hottest jobs worldwide in AI & Data.
Salary Growth
AI/ML Engineers earn ₹6–10 LPA (freshers) and ₹18–35 LPA (experienced professionals).
Career Roles
ML Engineer, Deep Learning Specialist, AI Engineer, Computer Vision Engineer, NLP Engineer.
Future-Proof Skills
Learn advanced ML + DL with real-world applications in vision, NLP, and generative AI.
Global Opportunities
High demand in Healthcare, FinTech, E-commerce, SaaS, Autonomous Systems, Startups.
Real Projects
Hands-on with image recognition, NLP chatbots, recommendation systems, and time-series forecasting.
The Companies That Want to Hire You
We Understand Your Struggles – And We’ve Solved Them!
Math & Coding Fear
- Afraid ML/DL needs too much math or coding?
- Learn with step-by-step Python + applied math made simple.
Too Many Algorithms
- Confused by Regression, SVMs, CNNs, RNNs, Transformers?
- Clear roadmap: ML → DL → Advanced Architectures.
No GPU Access
- Hardware is expensive for training deep models.
- We use Google Colab & free cloud GPU setups.
Interview Stress
- Can’t explain algorithms in interviews?
- Mock Q&A + case studies prepare you.
No Portfolio
- Nothing to showcase recruiters?
- Build 6+ ML & DL projects for your resume.
What Makes This Course Different
👉 Module Wise Quizzes, Assignments, and Practice Questions
👉 100% Placement assistance
👉 Industry professionals with 10+ years of experience
👉 Live Chat support assistance
👉 Access to session recordings for 2 years
👉 EMI Option also available with specified cards
Get ₹10,000 Worth of Free Career Booster Add-On Sessions
Dedicated Job Updates
100% Live Training in Telugu
Industry Ready Training
Interview Questions & Study Materials
Resume & Linked In Preparation
Machine Learning & Deep Learning Course Syllabus
1. Data Libraries
Introduction to NumPy
Creating Arrays, Indexing Arrays, Array Transposition
Universal Array Functions, Array Processing
Array Input/Output
Introduction to Pandas (Series, DataFrames)
Data Reading, Cleaning, Wrangling, Selection, Extraction with Pandas
Introduction to Matplotlib & Data Visualization
2. Mathematics
Linear Algebra
Statistics
Probability
Differential Calculus
3. Machine Learning
Introduction to Machine Learning
What is ML, Why ML?
Examples of ML Applications
Types of ML Systems (Supervised, Unsupervised, Batch vs Online, Instance vs Model Based)
Challenges of Machine Learning
Overfitting vs Underfitting
Phases of End-to-End ML Project
4. Classification Models
Binary Classifier
Performance Measures (Accuracy, Confusion Matrix, Precision, Recall, ROC Curve)
Multi-Class Classification
Error Analysis
Multi-Label & Multi-Output Classification
5. Regression Models
Linear Regression
Gradient Descent (Batch, Stochastic, Mini-Batch)
Polynomial Regression
Regularized Linear Models (Ridge, Lasso, Early Stopping)
Logistic Regression
6. Support Vector Machines
Linear SVM Classification
Soft Margin vs Hard Margin
Non-Linear SVM Classification
SVM Regression Models
7. Decision Trees
Introduction & Training Decision Trees
Visualizing Trees
Estimating Class Probabilities
CART Training Algorithm
Computational Complexity
Gini Impurity vs Entropy
Hyperparameter Regularization
Instability & Regression Trees
8. ASP.NET
Ensemble Learning
Voting Classifiers
Bagging & Pasting
Out-of-Bag Evaluation
Random Patches & Subspaces
Random Forests & Extra Trees
Feature Importance
Boosting (AdaBoost, Gradient Boost, Stacking)
9. Unsupervised Learning Techniques
Clustering
K-Means Algorithm & Limitations
Preprocessing with Clustering
Semi-Supervised Learning via Clustering
DBSCAN
10. Artificial Neural Networks with Keras
Biological Neuron & Perceptron
Multilayer Perceptron & Backpropagation
Regression & Classification MLPs
Implementing MLPs with Keras
Image Classifier with Sequential API
Regression MLP with Sequential API
Complex Models with Functional API
Saving/Restoring Models, Callbacks
Hyperparameter Tuning (Hidden Layers, Neurons, Batch Size, Learning Rate)
11. Deep Learning – Training Neural Networks
Vanishing/Exploding Gradients
Glorot & He Initialization
Non-Saturating Activation Functions
Batch Normalization
Gradient Clipping
Transfer Learning, Pretrained Layers
Unsupervised Pretraining
Faster Optimizers
Avoiding Overfitting (L1, L2, Dropout, Max-Norm)
12. Loading & Preprocessing Data with TensorFlow
Quick Tour of TensorFlow
Tensors & Operations vs NumPy
Data API & Chaining Transformations
Shuffling, Prefetching, Preprocessing Input Data
Encoding Features (One-Hot, Embeddings)
Keras Preprocessing Layers
TF Transform & TFDS Project
13. Generative AI Overview
Introduction to Generative AI
Architecture of Generative AI
Introduction to LLMs (Large Language Models)
Foundational / Public LLMs
Components of LLMs (Character Splitters, Embeddings, Vector Stores)
Role of RAGs (Retrieval Augmented Generation)
Prompt Engineering Basics
14. Capstone Project
End-to-End ML/DL Project with Real Dataset
Applying ML & DL Models to Real-World Problem
Model Optimization & Deployment
Documentation & Case Study Presentation
Real Projects You'll Build with Machine Learning
Sales Data Insights
Analyze sales data using preprocessing and visualization to uncover trends, patterns, metrics, and provide actionable business recommendations effectively.
AI-Based Resume Screener
Create an Machine learning tool to help HR teams automate resume screening using NLP techniques.
Melbourne Housing Snapshot
Investigate Melbourne housing market using machine learning models, predicting house prices with features like location, size, amenities, and trends.
Obesity Challenge
Predict obesity levels using health and lifestyle data with preprocessing, feature engineering, ML models, evaluating accuracy, and generating public health insights.
Financial Risk for Loan Approval
Develop a machine learning model predicting loan approvals using financial, credit, demographic data with classification, risk assessment, and insights.
FLM Bank Application
Create FLM Bank smart app using machine learning for predictive analytics, loan recommendations, retention, personalized offers, data preprocessing, and deployment.
Bank Statement Aggregator (BSA)
Design NLP-based system to process bank statements, analyze transactions, visualize spending habits, provide insights, and build scalable financial management solution.
Watch the Demo of Our Advanced Machine Learning Course in Telugu to Get a Preview of the Topics Covered.
Success Stories
Career Paths After Machine & Deep Learning Course
Freshers
📊 Data Analyst – ₹4–7 LPA
🤖 Junior ML Engineer – ₹5–9 LPA
🧠 AI Developer (Entry Level) – ₹6–10 LPA
✍️ Prompt Engineer (Beginner) – ₹5–8 LPA
💼 AI Associate / Research Intern – ₹4–6 LPA
Experienced
📊 Senior Data Analyst / BI Analyst – ₹10–18 LPA
🤖 ML Engineer / Deep Learning Specialist – ₹12–22 LPA
🧠 AI Developer (Mid to Senior Level) – ₹15–28 LPA
✍️ Prompt Engineer (Advanced) – ₹10–20 LPA
💼 Freelance AI Consultant / GenAI Specialist – ₹1L–2.5L per month
Complete Machine & Deep Learning Mastery in Telugu
- Time : 8:00-9:30PM , 4+ Months Duration
- Start Date: 22nd Mar 2025
Get ₹10,000 Worth of Free Career Booster Add-On Sessions
Resume Building
Create strong resumes with expert guidance.
Job Updates
Get access to latest openings & hiring alerts.
Interview Prep
Mock interviews and communication training.
LinkedIn Boost
Optimize your LinkedIn for visibility.
Freelancing
Learn how to start and grow as a freelancer.
Career Advancement Results
At Frontlines Edutech, we believe in transforming careers through high-quality, industry-relevant education. Our focus is on providing practical skills and knowledge that lead to real-world success. With a proven track record of impactful learning, we ensure our students are well-equipped to excel in their chosen fields and achieve their career goals with confidence.
Frequently Asked Questions
1. Do I need coding experience?
No! We start from complete basics and teach everything step-by-step.
2. Is the course really in Telugu?
100% Telugu instruction with English technical terms explained.
3. What if I miss live classes?
Every session recorded, 2-year access included.
4. Will I get job placement?
Yes! 100% placement assistance with resume, interview prep.
5. EMI options available?
Yes, flexible EMI starting ₹3,750/month.
Get Certified
Yes, you’ll get a Certificate representing your Industry Readiness once you submit your projects and clear the pre placement test.
Approved by AICTE
Certified by ISO 21001:2018
Recognized by Startup India
Registered under MSME
