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Data Science Course in Telugu: Master the AI Revolution & Command Top-Tier Salaries

Launch your career with this hands-on Data Science Course. Master Python, Machine Learning, and AI tools to become job-ready in just 4+ months

What is Data Science?

Data Science is the process of collecting, analyzing, and interpreting massive amounts of data to solve complex business problems. A Data Scientist uses programming and algorithms to predict what will happen next whether that is predicting a stock market crash, diagnosing a disease, or recommending a movie on Netflix.

The Evolution: Machine Learning, Deep Learning & NLP

We don’t just teach basic data analysis; we train you in advanced Artificial Intelligence.

Machine Learning (ML)

Training algorithms to learn patterns from historical data and make autonomous predictions (like fraud detection in banking).

Deep Learning (DL)

Building complex Neural Networks inspired by the human brain to process images, voice, and ultra-complex data.

Natural Language Processing

Teaching computers to understand, interpret, and generate human language (the exact technology behind ChatGPT and virtual assistants).

Generative AI & LLMs

Learn how AI models generate content, answer questions, and work with data using technologies behind ChatGPT, Gemini, and Claude.

Why Learn Data Science Course?

Modern QA is moving beyond manual testing. Companies now need testers who can validate UI, APIs, databases, automation workflows and use AI-powered tools to deliver faster, smarter and more reliable software.

Unprecedented Industry Demand

Startups, global banks, ecommerce giants, and healthcare networks are in a desperate bidding war for professionals who can build AI-powered systems.

Future-Proof Your Career:

Traditional coding jobs are being automated, but Data Scientists are the ones building the automation. This is the safest, most future-proof career in tech.

Massive Salary Opportunities

Because AI directly drives revenue and efficiency, specialized roles like Machine Learning Engineer and AI Engineer command the highest paychecks in the industry.

Global Remote Opportunities

AI infrastructure lives in the cloud. You can build, train, and deploy predictive models for international clients entirely remotely.

Tools & Technologies You Will Learn in Data Science Course

We train you on the exact tools required by top product-based companies and global IT service giants:

Python Programming

The undisputed language of AI. We start from absolute zero, teaching you how to use Python, Pandas, and NumPy to process and manipulate massive datasets effortlessly.

SQL & Data Analytics

Learn to query corporate databases to extract the exact data you need before feeding it into your AI models.

Machine Learning (Scikit-Learn)

Master supervised and unsupervised learning. Build regression and classification models to predict pricing, customer churn, and business trends.

Deep Learning (TensorFlow & Keras)

Step into advanced AI. Build powerful Neural Networks that can recognize images, predict complex sequences, and automate heavy enterprise tasks

Natural Language Processing (NLP)

Master the technology behind modern chatbots. Learn text processing, sentiment analysis, and how to build AI systems that understand human language.

Model Deployment

Deploy machine learning models into real applications and learn the basics of APIs, model monitoring, and production-ready AI workflows.

Your Roadmap to Master Data Science Course

1. PYTHON INTRODUCTION & ENVIRONMENT SETUP

Introduction, Roadmap
Program Execution – programmer’s view, Python’s view
Installation
Python
PyCharm, VS Code, Jupyter Notebook
Setup, configure Python in Laptop

2. PYTHON FUNDAMENTALS

All Numeric types in Python
Python Variables, objects, References, Shared References
Garbage Collection of objects
Strings, Lists, Dictionaries, Tuples, sets, Files
Assignments, Expressions and Prints
if-else, if-elif-else, if-else ternary expression
while and for loops
Comprehensions
map and zip functions
range, len, enumerate

3. FUNCTIONS & ADVANCED PYTHON

Python Functions – def, nested functions
Variable Scopes – LEGB rules, global, nonlocal
Function Arguments
Lambda functions
Generators and comprehensions
Generator functions, yield statement
Generator expression

4. PYTHON MODULES

Python Modules
Definition, why modules?
Typical Python program architecture
Import statement
How Import works: Find it, Compile it, Run it
Standard library modules
pycache folder for byte code files
Module search path
Other import statements
Module packages
Mixed usage modes: name and main
The as extension for import and from

5. OBJECT ORIENTED PROGRAMMING

Introduction to Python Classes
Why Classes?
Classes, constructors and Instances
Method calls
Static and class methods
Subclassing by Inheritance
Polymorphism in Action
Class vs instance attributes
Abstract super classes
Nested classes

6. OPERATOR OVERLOADING & EXCEPTION HANDLING

Operator Overloading
Constructors: init
Indexing, Slicing: getitem and setitem
String Representation: repr and str
Inheritance: “IS-a” relationship
Composition: “HAS-a” relationship
Exception Basics
Default Exception handler
Catching Exceptions
Raising Exceptions
try/except/else statement
raise statement
with/as context managers
Built-in Exception Classes
Custom Exceptions

7. REGULAR EXPRESSIONS

What are regular expressions?
regex module in python
The match Function
The search Function
Matching vs searching
Search and Replace
Meta characters, advanced patterns

8. NUMPY & PANDAS

Introduction to numpy
Creating arrays
Indexing Arrays
Array Transposition
Universal Array Function
Array Processing
Array Input and Output
Introduction to Pandas, Series, Dataframes
Data reading with Pandas
Data cleaning with Pandas
Data selection with Pandas
Data extraction with Pandas

9. MATHEMATICS FOR DATA SCIENCE

Linear Algebra
Statistics
Probability
Differential Calculus

10. MACHINE LEARNING FUNDAMENTALS

What is Machine Learning
Why use Machine Learning
Examples of ML applications
Types of ML Systems
Supervised Learning
Unsupervised Learning
Instance-based vs Model-based Learning
Challenges of Machine Learning
Overfitting vs underfitting training data
End to End ML Project

11. CLASSIFICATION & REGRESSION MODELS

Binary Classifier
Performance Measures
Accuracy
Confusion Matrix
Precision and Recall
Multi Class Classification
Multi Label Classification
Linear Regression
Gradient Descent
Batch Gradient Descent
Stochastic Gradient Descent
Mini-batch Gradient Descent
Polynomial Regression
Regularized Linear Models
Lasso Regression
Early Stopping
Logistic Regression

12. DECISION TREES & RANDOM FORESTS

Introduction to Decision Tree
Training Decision Tree
Visualizing Decision Tree
Estimating Class Probabilities
CART Training Algorithm
Gini Impurity vs Entropy
Regularization of Hyperparameters
Ensemble Learning
Voting Classifiers
Random Forests

13. UNSUPERVISED & DEEP LEARNING

Clustering
K-Means Algorithm and Limits of K-Means
KMeans++
Introduction to Artificial Neural Networks with Keras
Biological Neuron
The Perceptron
Multilayer Perceptron and Back propagation
Regression MLPs
Classification MLPs
Implementing MLPs with Keras
Building an Image classifier using Sequential API
Building Regression MLP using sequential API
Saving and Restoring Model

14.ADVANCED DEEP LEARNING & CAREER SUPPORT

Fine tuning neural network hyper parameters
Number of Hidden layers
Number of neurons per hidden layer
Learning rate, Batch size and other hyper parameters
Training Deep Neural Networks
Vanishing/Exploding Gradients problems
Glorot and He initialization
Batch Normalization
Transfer Learning
Avoiding overfitting through Regularization
Dropout
MC (Monte Carlo) Dropout
Resume Building
Daily Assignments
LinkedIn Profile Building
Interview Guidance
Q&A Sessions
Placement Updates
Downloadable Resources
Top Companies Hiring

Real Projects Where You'll Build on This Course

Obesity Risk Prediction Using Machine Learning

Build an AI model to predict obesity risk based on lifestyle and health-related survey data. Compare multiple machine learning algorithms and identify the model that gives the best prediction accuracy.

Tools Used:

Python · Pandas · NumPy · Scikit-learn · Random Forest · SVM · ANN · KNN

01

Financial Risk Prediction for Loan Approval

Analyze customer financial data to predict loan approval chances and estimate financial risk. Use classification and regression models to understand borrower profiles and support smarter lending decisions.

Tools Used:

Python · Pandas · NumPy · Regression Models · Data Visualization

02

Analysis of Capitals and Universities Data

Analyze university and country datasets to identify education trends, rankings, and geographical patterns. Work with structured CSV data and extract useful insights through data analysis.

Tools Used:

Python · Pandas · CSV Handling · Data Analysis

01

Online Shopping System

Build a Python-based shopping cart system using OOP concepts. Implement product selection, GST calculation, invoice generation, order summary, and basic transaction workflows.

Tools Used:

Python · OOP Concepts · Functions · File Handling

02

Analytic American Association

Develop a law firm management system to manage clients, lawyers, billing, invoices, and daily operations. Apply Python OOP and file handling to automate common administrative workflows.

Tools Used:

Python · OOP Concepts · File Handling · Data Management

03

Sales Data Insights

Analyze sales datasets to understand revenue trends, customer behavior, product performance, and business patterns. Use data libraries and visualizations to convert raw sales data into useful insights.

Tools Used:

Python · Pandas · NumPy · Data Visualization

04

Why This Data Science Course Is Your Best Bet

👉 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

👉 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

Career & Job Readiness Support

Every program includes industry-focused add-on sessions designed to help students crack jobs, freelance, switch careers, and grow professionally.

Career Acceleration Ecosystem

Everything you need beyond coding to become job-ready.

Resume Building

Session 01

LinkedIn Optimization

Session 02

Freelancing

Session 03

Career Switch Guidance

Session 04

Job Search Strategy

Session 05

Financial Awareness

Session 06

MAANG Preparation

Session 07

Agile & Scrum Workflow

Session 08

Git & GitHub

Session 09

HR + Salary Negotiation

Session 10

Communication Bootcamp

Session 11

Complete Data Science Mastery in Telugu Course Fee

Actual Price

Rs. 49,999/-

Special Price

Rs.17,999/-

Saving price

Rs. 32,000/-

Watch the FLM Demo of Our Data Science Course in Telugu to Get a Preview of the Topics Covered.

What Our Data Science Students Say

Career Paths After Learning Data Science Course

Job Role

Experience

Average Salary

Fresher Salaries

Data Analyst

Fresher

₹4 – ₹8 LPA

Data Scientist

Fresher

₹6 – ₹12 LPA

ML Engineer

Fresher

₹4 – ₹12 LPA

AI Engineer / Architect

Fresher

₹3 – ₹4 LPA

Deep Learning Specialist

Fresher

₹5 – ₹8 LPA

Job Role

Experience

Average Salary

Experienced Salaries

Data Analyst

3–5 Years

₹12 – ₹18 LPA

Data Scientist

5–8 Years

₹20 – ₹40 LPA

ML Engineer

4–6 Years

₹15 – ₹30 LPA

AI Engineer / Architect

5–8 Years

₹12 – ₹25 LPA

Deep Learning Specialist

4–6 Years

₹15 – ₹28 LPA

Companies That Want to Hire You

Our Results Speak for Themselves

At Frontlines Edutech, we don’t just teach we transform careers. Our Data Science Course is designed to give you the practical skills and confidence needed to not only land a job but also excel in your chosen field.

Happy Students

0 k+

Batches Conducted

0 +

Years of Experience

0 +

Satisfaction

0 %

Frequently Asked Questions

1. Do I need a strong background in Mathematics or heavy coding knowledge to learn AI?

No! While Data Science involves math, modern Python libraries and LLM frameworks (like LangChain and TensorFlow) do the complex mathematical calculations for you. We teach you the logic behind the systems and how to apply them. You do not need a Ph.D. to become a highly paid AI Engineer.

2. I am from a non-IT background (B.Com, BBA, B.Sc). Is this a good career path for me?

Absolutely. In fact, English and logical thinking are the new programming languages. Prompt Engineering and AI Automation are the fastest ways for non-IT students to bypass traditional coding roles and secure high-paying tech salaries. We teach you Python from absolute zero.

3. Are the live training classes conducted in Telugu?

Yes! All sessions, practical model training, and doubt-clearing classes are taught in Telugu. We break down complex Machine Learning algorithms and GenAI frameworks in your regional language to ensure absolute conceptual clarity.

4. What is the difference between Data Analytics and Data Science?

A Data Analyst looks at past data to explain what happened (using tools like SQL and Power BI). A Data Scientist builds AI and Machine Learning models to predict what will happen in the future. This course takes you to the advanced, predictive level.

5. What are Machine Learning and Deep Learning?

Machine Learning is training a computer to recognize patterns in data so it can make decisions without being explicitly programmed. Deep Learning is an advanced form of ML that uses “Neural Networks” (inspired by the human brain) to handle ultra-complex tasks like image recognition and ChatGPT-style language processing.

6. Will I actually build real AI models, or is this just theory?

This course is entirely project-driven. You will process real-world datasets and build live AI models—including RAG Document Assistants, Loan Risk Predictors, and Custom AI Chatbots—to showcase directly to hiring managers on your GitHub.

7. What is the starting salary for a Data Scientist or ML Engineer in India?

Because AI directly drives massive corporate revenue, professionals are paid a premium. Freshers can expect starting salaries between ₹6 LPA and ₹12 LPA. With Deep Learning expertise and experience, salaries rapidly scale to ₹25 LPA to ₹50 LPA+.

8. Can I work internationally or remotely after learning Data Science?

Yes. AI and Data Science are universally demanded skills. Companies worldwide are desperate for talent. You can work remotely, take on lucrative international consulting contracts, or participate in global predictive modeling competitions like Kaggle.

9. Do you provide placement assistance?

Yes. We provide comprehensive placement support. This includes aggressive GitHub portfolio reviews, building an ATS-friendly AI professional resume, conducting live technical mock interviews, and providing direct job updates for top tech companies.

10. Will I receive a certificate after completing the course?

Yes. Upon successfully completing the training and deploying your real-time AI and Machine Learning projects, you will receive an industry-recognized certificate from Frontlines EduTech to massively boost your LinkedIn profile and resume credibility.

Get Certified

Yes, you’ll get a Certificate representing your Industry Readiness once you submit your projects and clear the pre placement test.

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