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⭐ Most Enrolled Course 📍 Dilsukhnagar, Hyderabad ✅ Certificate on Completion

Data Science Course

The most comprehensive Data Science course in Hyderabad — 12 weeks, taught by an active Senior Data Scientist working at an MNC with 8+ years of experience. From Python basics to deploying ML models in production. Real projects, real data, real career outcomes.

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DURATION

12 Weeks

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LEVEL

Beginner to Advanced

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MODE

Online · Offline · Hybrid

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CERTIFICATE

Industry Certificate

Tools & Technologies You Will Learn

Python Pandas NumPy Matplotlib Seaborn Scikit-learn TensorFlow Keras PyTorch NLTK Spacy Power BI SQL Tableau Jupyter Git

Enroll on WhatsApp → View Curriculum

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Free Demo Available
Contact us for current batch fees & EMI options

⏱ Duration: 12 Weeks
🎯 Level: Beginner to Advanced
💻 Online · Offline · Hybrid
🏆 Certificate on completion
💼 100% placement assistance
📁 Real project + internship
🔁 Lifetime access to recordings
📞 Mentor support throughout

Enroll Now on WhatsApp Book Free Demo Class Call: +91 93900 23585

Free career counselling available daily · No pressure, just honest advice

About This Course

Why Data Science remains the most reliable path into high-paying tech careers

While new AI roles emerge every year, Data Science remains the foundation of all of them. Every Generative AI system, every AI agent, every ML model in production — all of it is built on data. Companies across every industry in India and globally are actively hiring Data Scientists, Data Analysts and ML Engineers right now. The demand has not slowed — it has accelerated, because AI adoption requires more data professionals, not fewer.

At LearnAI Tech Hub, this 12-week course is structured around the exact progression that a Data Scientist follows in a real company — from data cleaning and exploration, through statistical analysis and ML model building, to deep learning, NLP and deployment. Every week includes a real project. By week 12, you have a portfolio of 12 complete projects across 6 different domains — the strongest interview asset you can carry into the job market.

What makes this course different

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Taught by an active Senior Data Scientist — 8+ years at MNC

Your trainer builds and deploys ML models for enterprise clients every day. Every dataset, every project and every architectural decision comes from real production experience.

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12 real projects — one per week

Not toy datasets. Real-world datasets from healthcare, finance, e-commerce and logistics — the same types of problems you will face in your first job.

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AI integrated throughout

Every module includes how AI tools (ChatGPT, GitHub Copilot, Claude) accelerate Data Science workflows — so you graduate working the way industry professionals work in 2026.

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Most consistent placement rate of any LearnAI course

Data Scientists are hired across every industry — IT, healthcare, banking, e-commerce, logistics, consulting. Our placement team has the widest industry reach for this course.

Course Curriculum

9 modules · 12 Weeks · Real projects every week

Every module is taught by an active MNC professional using real tools, real datasets and real architectures — not textbook examples.

Python for Data Science

12 topics · Weeks 1–2

Python fundamentals: variables, data types, control flow, functions

NumPy: arrays, operations, broadcasting and vectorisation

Pandas: DataFrames, data cleaning, transformation and aggregation

Data types: CSV, JSON, Excel, SQL — loading and saving

String operations, datetime handling and data type conversions

Project: Clean and analyse a real-world messy dataset from scratch

Exploratory Data Analysis & Visualisation

10 topics · Week 3

Descriptive statistics: mean, median, variance, distributions

Matplotlib and Seaborn for publication-quality charts

Univariate, bivariate and multivariate analysis

Correlation analysis and feature relationships

Handling missing values, outliers and data imbalance

Project: Full EDA report on a real business dataset

Statistics for Data Science

10 topics · Week 4

Probability fundamentals and distributions

Hypothesis testing: t-tests, chi-square, ANOVA

Central Limit Theorem and sampling theory

Confidence intervals and p-values explained clearly

Regression foundations: linear and logistic

Project: Statistical analysis and business insight report

Machine Learning — Supervised Learning

14 topics · Weeks 5–6

ML workflow: problem definition, data prep, model selection, evaluation

Linear and Logistic Regression — implementation and interpretation

Decision Trees, Random Forest, Gradient Boosting

Support Vector Machines and K-Nearest Neighbours

Model evaluation: accuracy, precision, recall, F1, ROC-AUC

Project: Customer churn prediction model for a telecom dataset

Machine Learning — Unsupervised & Advanced

10 topics · Week 7

K-Means, DBSCAN and hierarchical clustering

PCA and dimensionality reduction

Anomaly detection for fraud and quality control

XGBoost, LightGBM — top competition algorithms

Hyperparameter tuning: GridSearch, RandomSearch, Optuna

Project: Customer segmentation system for e-commerce

Deep Learning with TensorFlow & PyTorch

12 topics · Weeks 8–9

Neural networks from scratch — perceptrons, activations, backprop

TensorFlow and Keras for practical deep learning

Convolutional Neural Networks (CNNs) for image data

Recurrent Neural Networks (RNNs) and LSTMs for sequences

Transfer learning with pre-trained models

Project: Image classification system for medical diagnosis

Natural Language Processing (NLP)

10 topics · Week 10

Text preprocessing: tokenisation, stemming, lemmatisation

TF-IDF, word embeddings, Word2Vec, GloVe

Sentiment analysis and text classification

Named Entity Recognition (NER) with SpaCy

Transformer models: BERT for NLP tasks

Project: Sentiment analysis system for product reviews

Data Visualisation & Business Intelligence

8 topics · Week 11

Power BI: data modelling, DAX formulas, interactive dashboards

Tableau basics for visual analytics

Storytelling with data — communicating insights to business stakeholders

SQL for data extraction and aggregation

Connecting Python analysis to BI dashboards

Project: Executive dashboard for a real business dataset

ML Deployment & Career Preparation

10 topics · Week 12

Model deployment with Flask, FastAPI and Streamlit

MLOps basics: model versioning, monitoring and retraining

Cloud deployment: AWS SageMaker, Azure ML basics

Portfolio documentation and GitHub best practices

Data Science interview preparation — technical and case study rounds

HR placement referral and mock interviews

Get Full Curriculum on WhatsApp →

Career Outcomes

Roles you will qualify for after this course

Our placement team directly places students from this course into these roles across our 1,000+ client company network — startups to Fortune MNCs.

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Data Scientist

₹6L – ₹18L / year

IT companies, BFSI, e-commerce, healthcare, analytics firms across India, USA, UK, Australia

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Machine Learning Engineer

₹7L – ₹20L / year

AI product companies, tech startups, Fortune companies with AI/ML teams

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Data Analyst

₹4L – ₹12L / year

Every industry — banking, retail, healthcare, logistics, consulting, EdTech

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Business Intelligence Analyst

₹5L – ₹14L / year

BFSI, e-commerce, consulting firms, operations analytics teams

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Healthcare Data Analyst

₹5L – ₹15L / year

Hospitals, healthcare tech companies, pharma, insurance companies

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AI Research Analyst

₹8L – ₹22L / year

AI labs, R&D departments, Fortune companies, consulting firms

Average Starting Salary — Freshers (Hyderabad)

Based on our placed students · 2024–2025 batch data

₹5L – ₹18L per year

Who Is This For

This course is designed for you if…

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Fresh graduates from any degree — B.Tech, BCA, BSc, BBA, MBA

Data Science is one of the most accessible high-paying careers for graduates from any background. Your domain knowledge + data skills = a unique advantage in domain-specific Data Science roles.

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Working professionals looking to switch to tech

Data Science is one of the most successful career switch paths — especially for professionals already working in finance, healthcare, marketing or operations who can combine domain expertise with data skills.

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Excel and SQL users wanting to level up

If you are already working with data in Excel or SQL, this course gives you the Python and ML skills to move from data analyst to data scientist — a significant salary and career jump.

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Domain specialists — doctors, engineers, finance professionals

A financial analyst who knows ML is a Financial Data Scientist. A doctor who knows healthcare AI is a Healthcare Data Analyst. Your domain knowledge makes you far more valuable than a generic data scientist.

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Developers who want to move into AI/ML

If you code but want to work on the AI and data side — this course gives you the complete transition path from software development into Data Science and ML engineering.

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Final year B.Tech / M.Tech students

A Data Science capstone project with a real dataset in your portfolio will get you noticed in placements in a way that a standard college project simply will not.

Prerequisites

Basic computer literacy Any graduation or final year student No programming experience needed — Python taught from scratch Interest in working with numbers and data

FAQs

Questions about Data Science Course?

Not finding your answer? WhatsApp us directly — we respond within 30 minutes.

Ask on WhatsApp →

Do I need to know programming before joining the Data Science course?

No. The course begins with Python fundamentals from absolute scratch. If you have never written a single line of code, you can still join and follow through to the end. The first two weeks are dedicated entirely to Python for Data Science before any ML concepts are introduced.

Is Data Science still a good career in 2026?

Absolutely. Data Science demand has not slowed — it has accelerated. AI adoption requires more data professionals, not fewer. Every company building AI systems needs people who understand data — how to collect it, clean it, analyse it and build models on it. Data Scientists with ML and AI integration skills are among the most consistently hired professionals across industries.

How many projects will I build during the course?

12 projects — one per week. Real datasets, real business problems. By week 12 your portfolio includes projects across healthcare (medical image classification), finance (fraud detection), e-commerce (customer segmentation), telecom (churn prediction), retail (sales forecasting) and NLP (sentiment analysis).

What is the average salary for a Data Scientist in Hyderabad?

Freshers typically start at ₹4L–₹8L per year depending on the company and role. With 2–3 years of experience, salaries move to ₹10L–₹18L. At senior levels and in MNCs, salaries reach ₹20L+ per year. Our HR team has current placement data and shares specific salary benchmarks during career counselling.

Can working professionals join this course?

Yes. Weekend batches (Sat–Sun) and evening batches (7PM–9PM weekdays) are specifically designed for working professionals. Online mode allows you to join from anywhere without affecting your current job.

Will I get placement support after the course?

Yes. Our 50+ HR team actively places Data Science graduates in companies across India, USA, UK, Australia and UAE. You receive ATS resume building, LinkedIn profile optimisation, multiple mock interview rounds and direct placement referral to our 1,000+ client company network.

Data Science Course

Why Data Science remains the most reliable path into high-paying tech careers

Taught by an active Senior Data Scientist — 8+ years at MNC

12 real projects — one per week

AI integrated throughout

Most consistent placement rate of any LearnAI course

9 modules · 12 Weeks · Real projects every week

You will graduate using industry tools — not toy projects

Roles you will qualify for after this course

This course is designed for you if…

Fresh graduates from any degree — B.Tech, BCA, BSc, BBA, MBA

Working professionals looking to switch to tech

Excel and SQL users wanting to level up

Domain specialists — doctors, engineers, finance professionals

Developers who want to move into AI/ML

Final year B.Tech / M.Tech students

Prerequisites

Questions about Data Science Course?

Enroll in Data Science Course today

Data Science Course

Why Data Science remains the most reliable path into high-paying tech careers

Taught by an active Senior Data Scientist — 8+ years at MNC

12 real projects — one per week

AI integrated throughout

Most consistent placement rate of any LearnAI course

9 modules · 12 Weeks · Real projects every week

You will graduate using industry tools — not toy projects

Roles you will qualify for after this course

This course is designed for you if…

Fresh graduates from any degree — B.Tech, BCA, BSc, BBA, MBA

Working professionals looking to switch to tech

Excel and SQL users wanting to level up

Domain specialists — doctors, engineers, finance professionals

Developers who want to move into AI/ML

Final year B.Tech / M.Tech students

Prerequisites

Questions about Data Science Course?

Enroll in Data Science Course today

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