Data Science + GenAI + Agentic AI · Kukatpally, Hyderabad
Data Science Course in Kukatpally — with Generative AI & Agentic AI
Learn Data Science from zero at The Data School in KPHB Colony, Kukatpally. Start with Python, move through statistics, SQL, machine learning and deep learning, then build LLM apps, RAG systems and AI agents — creating portfolio projects on real datasets as you go.
- 16 modules
- 102 topics
- Course fee ₹30,000
- Batches 9:30 AM – 11:30 AM · 11:30 AM – 1:30 PM
- Classroom · Online · Hybrid
- KPHB Colony, Kukatpally
Why The Data School
Why learn Data Science at our Kukatpally centre
- 01
Starts from your first line of code
No prior programming is needed. Python is taught from the basics, so freshers and non-IT graduates can follow every module.
- 02
Data Science + GenAI + Agentic AI
Python, statistics, SQL, machine learning, deep learning, NLP, generative AI, RAG and AI agents in one structured program.
- 03
Projects you can show
Every module is paired with hands-on exercises, and the program builds to end-to-end portfolio projects you can publish on GitHub.
- 04
Close to home
Classroom batches in KPHB, a short walk from KPHB Metro, with live online and hybrid options when you can't travel.
What you'll learn
Data Science + GenAI + Agentic AI syllabus
The modules you'll cover, in order. Expand the full syllabus for every topic.
- 01
Python for Data Science
Learn the Python fundamentals you will use every day as a data professional.
Installing Python and Jupyter · Variables, data types and operators · Conditionals and loops · Functions and modules · Lists, tuples, dictionaries and sets
- 02
NumPy & Pandas
Load, clean and reshape data efficiently with the core Python data libraries.
NumPy arrays, indexing and broadcasting · Series and DataFrames · Loading CSV, Excel and JSON · Cleaning missing and duplicate data · Filtering, sorting and groupby
- 03
Data Analysis & Visualization
Explore datasets and communicate what you find with clear, honest charts.
The EDA workflow · Matplotlib · Seaborn · Distributions, correlations and outliers · Choosing the right chart
- 04
Statistics
Build the statistical reasoning needed to draw reliable conclusions from data.
Descriptive statistics · Probability and distributions · Sampling and the central limit theorem · Confidence intervals · Hypothesis testing and p-values
- 05
SQL for Analytics
Query relational databases confidently to answer real business questions.
Relational concepts · SELECT, WHERE and ORDER BY · Aggregations and GROUP BY · Joins · Subqueries and CTEs
- 06
Machine Learning
Train, validate and compare your first supervised and unsupervised models.
Supervised vs unsupervised learning · Linear and logistic regression · Decision trees and k-NN · Train/test split and cross-validation · Accuracy, precision, recall and RMSE
- 07
Advanced Machine Learning
Improve model performance with ensembles, better features and careful tuning.
Random forests and gradient boosting · Feature engineering and selection · Hyperparameter tuning · Handling imbalanced data · PCA
- 08
Deep Learning & AI Foundations
Understand how neural networks learn and how they power modern AI.
Neurons, layers and activations · Backpropagation and gradient descent · Building networks in PyTorch · Overfitting and regularisation · Intro to CNNs and sequence models
- 09
Natural Language Processing
Turn unstructured text into features, classifications and insights.
Text preprocessing and tokenisation · Bag of words and TF-IDF · Word embeddings · Text classification and sentiment analysis · Named entity recognition
- 10
Generative AI Foundations & Prompt Engineering
Understand how large language models work and write prompts that produce reliable output.
What generative AI is · Transformers and LLMs at a high level · Tokens, context windows and hallucinations · Zero-shot and few-shot prompting · Chain-of-thought
- 11
LLM Applications, Embeddings & Vector Search
Integrate LLMs into software and represent meaning as vectors to power search.
Calling LLM APIs · System prompts and parameters · Function / tool calling · Embeddings and similarity · Vector databases and chunking
- 12
Retrieval Augmented Generation (RAG)
Ground model answers in your own data, and measure the quality of what comes back.
RAG architecture · Ingestion pipelines · Retrieval and re-ranking · Context construction · Reducing hallucinations and citing sources
- 13
Agentic AI Foundations & Tool Calling
Understand what makes a system agentic and give agents safe abilities to act.
Agents vs chatbots · The perceive-plan-act loop · Reasoning and planning patterns · Tool schemas and function calling · Calling external APIs and databases
- 14
Agent Workflows, Memory & Multi-Agent Systems
Structure multi-step work, manage memory and coordinate specialised agents.
Workflows vs autonomous agents · Task decomposition, retries and fallbacks · Human-in-the-loop · Short and long-term memory · RAG as an agent tool
- 15
AI Evaluation, Safety & Guardrails
Keep generative and agentic systems measurable, safe and cost-controlled.
Evaluating LLM and agent outputs · Test sets and success metrics · Prompt injection · Input / output guardrails · Logging and observability
- 16
Portfolio Projects
Bring everything together in end-to-end data science and AI projects you can show employers.
Problem framing and data collection · Cleaning, EDA and modelling · Building a RAG assistant · Building an AI agent · Publishing to GitHub
Who it's for
Built for learners in Hyderabad
- B.Tech, B.Sc, BCA, MCA and other graduates from Hyderabad colleges
- Freshers who want to start a career in data
- Working professionals in IT or non-IT roles planning a switch
- Analysts who want to move into machine learning
Tools & technologies
- Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
- SQL
- Scikit-learn
- PyTorch
- NLP
- LLMs
- Embeddings
- Vector Databases
- RAG
- AI Agents
Roles these skills are relevant to
- Data Scientist
- Machine Learning Engineer
- Generative AI Engineer
- Agentic AI Engineer
Outcomes depend on individual effort, background and the job market.
Visit us
Data Science course in Kukatpally — classes in KPHB Colony, Kukatpally
Classroom training at our centre in KPHB Colony, Kukatpally — close to KPHB Metro, JNTU, Nizampet, Miyapur and Hitech City.
The Data School — KPHB, Hyderabad
4th Floor, MIG 549, Road Number 1, Above HDFC Bank, KPHB Colony Phase 2, Kukatpally, Hyderabad, Telangana 500072
Monday–Saturday, 9:00 AM – 9:00 PM (Sunday closed)
Landmarks
- 4th Floor, MIG 549
- Road Number 1, KPHB Colony
- Above HDFC Bank
- Near Prime Hospitals
- Opposite GHMC Park
Getting here
By Metro
Take the Red Line (Miyapur – LB Nagar) to KPHB Colony station, then head to Road Number 1 in KPHB Colony. Look for HDFC Bank — our centre is in the same building, above the bank.
From JNTU, Nizampet & Bachupally
Come into KPHB Colony and take Road Number 1. The centre is above HDFC Bank, near Prime Hospitals and opposite GHMC Park.
From Miyapur, Hitech City & Kondapur
Travel towards Kukatpally / KPHB Colony and turn onto Road Number 1. Use “Get directions” for turn-by-turn navigation to our Google Maps listing.
First visit?
Call +91 96664 47822 before you set off and we'll guide you in. Open Monday–Saturday, 9:00 AM – 9:00 PM (Sunday closed).
FAQ
Questions, answered
Still unsure? An advisor is happy to help.
Is this Data Science course suitable for non-IT students in Kukatpally?
Yes. The course assumes no prior coding. Python is taught from the beginning, and comfort with basic computer use and school-level maths is enough to start.
Where are Data Science classes held?
Classroom sessions run at our centre: 4th Floor, MIG 549, Road Number 1, Above HDFC Bank, KPHB Colony, Kukatpally, Hyderabad. Live online and hybrid modes are also available.
Does the Data Science course include Generative AI and Agentic AI?
Yes. After machine learning, deep learning and NLP, the course covers prompt engineering, LLM applications, embeddings and vector search, RAG, AI agents with tool calling, multi-agent systems and guardrails.
Will I build projects during the course?
Yes. You practise every concept in code, and the course ends with end-to-end portfolio projects such as customer churn prediction, a RAG assistant and an AI agent that you can show employers.
Is there a free demo class for Data Science in Kukatpally?
Yes. Book a free demo class at our KPHB centre or online — there's no obligation to enrol. You can also call or WhatsApp us on +91 96664 47822.
What is the course fee, and when do batches start?
The course fee is ₹30,000. Classroom batches run Monday to Saturday, 9:30 AM – 11:30 AM or 11:30 AM – 1:30 PM. You can attend a free demo class first — book one online or call the centre, and an advisor will share the next start date.
Courses near you
KPHB & Kukatpally
Hyderabad
Start your journey in KPHB.
Speak with an advisor about the right program, learning modes, fees and upcoming batches.