Build models that predict what happens next
Our Data Science course in Hyderabad takes you from Python and statistics to machine learning, deep learning and deployment, with end-to-end projects you can show employers.
Ask SMALL i about this course →What is data science?
Data science combines programming, statistics and domain knowledge to find patterns in data and use them to predict or decide.
Collect, clean and shape messy data into something a model can learn from.
Visualise and test ideas to understand what drives the outcome.
Train machine learning and deep learning models to predict results.
Put models behind an API and keep an eye on how they perform.
A bank wants to spot risky loans, a shop wants to forecast demand. A data scientist frames the problem, builds the model, tests it honestly and helps the team use it.
The six steps of every project
The lifecycle you will repeat on every project in the course.
Turn a business problem into a question data can answer.
Gather, clean and engineer features from raw data.
Chart, test and understand the patterns.
Train and tune algorithms for the task.
Measure results fairly and avoid fooling yourself.
Serve the model and track it over time.
11 modules in our Data Science course in Hyderabad
Open any module to see what you will learn. Modules marked Hands on include practical lab work.
01Introduction to Data Science
- Data Science Lifecycle, Roles, and Tools
- Problem Framing, CRISP-DM Methodology
02Python for Data ScienceHands on
- Python Basics, OOP, File Handling, Virtual Environments
- NumPy, Pandas, Data Wrangling
- Jupyter Notebooks, Git and GitHub
03Mathematics and Statistics
- Linear Algebra, Calculus Basics for ML
- Probability, Distributions, Sampling
- Hypothesis Testing, Confidence Intervals
04SQL and Data HandlingHands on
- SQL Querying, Joins, Window Functions
- Working with APIs and Web Scraping
- Data Cleaning and Feature Engineering
05Data Visualization and EDAHands on
- Matplotlib, Seaborn, Plotly
- Exploratory Data Analysis Techniques
06Machine LearningHands on
- Supervised Learning: Linear and Logistic Regression, Decision Trees, Random Forest, SVM, KNN
- Ensemble Methods: Bagging, Boosting, XGBoost, LightGBM
- Unsupervised Learning: K-Means, Hierarchical, DBSCAN, PCA
- Model Evaluation, Cross Validation, Hyperparameter Tuning
07Deep Learning
- Neural Networks, Backpropagation, Activation Functions
- CNNs, RNNs, LSTMs with TensorFlow and PyTorch
- Transfer Learning
08Natural Language Processing
- Text Preprocessing, TF-IDF, Word Embeddings
- Sentiment Analysis, Text Classification
- Transformers and Large Language Models Overview
09Time Series and Recommender Systems
- ARIMA, Prophet, Forecasting Techniques
- Collaborative and Content-Based Filtering
10MLOps and Deployment
- Model Deployment with Flask and FastAPI
- Docker Basics, Experiment Tracking with MLflow
- Cloud Deployment Overview
11Capstone Projects
- End-to-End Projects, Portfolio, and Interview Preparation
Tools you will use in our Data Science course in Hyderabad
The tools used in real projects and listed in most job descriptions.
Why learn data science
Skills that stay useful as tools and trends change.
Forecasting, recommendations, language and vision all use the same toolkit.
Finance, health, retail and logistics all build models.
Maths, statistics and Python skills carry over to AI roles.
Move toward ML engineering, research or leadership.
Learn deployment so your models leave the notebook.
Great step up if you already know SQL or BI tools.
Roles you can aim for
Titles vary by company, but these are common starting points and next steps.
Frames problems, builds models and explains results.
Python · ML · StatisticsTurns models into reliable production services.
Python · FastAPI · DockerUses models inside business teams for forecasts and scoring.
Python · SQLWorks with text, search and language models.
Python · NLPPredicts demand, sales and capacity over time.
Time series · PythonGuides clients from idea to a working solution.
Python · CommunicationWhat you will be able to do
A balance of technical ability and the habits employers look for.
- Python and SQL: wrangle and query data confidently.
- Machine learning: regression, trees, ensembles and clustering.
- Deep learning: neural networks, CNNs, RNNs and transfer learning.
- Deployment: APIs, Docker and experiment tracking.
- Statistics: sampling, testing and confidence in results.
- Problem framing: ask the right question before modelling.
- Honest evaluation: validate models and avoid overfitting.
- Explaining results: tell the story to non-technical people.
Build a portfolio you can show
Capstone work and interview preparation are part of the course.
Take a problem from raw data to a deployed model.
Classify text with NLP techniques.
Predict future values with time series methods.
Suggest items using collaborative and content-based methods.
Present your work clearly on GitHub and in your resume.
Practise concept and case questions.
Who this Data Science course in Hyderabad is for
You do not need to be an expert to begin.
From any stream with an interest in data and AI.
Data analysts ready to add modelling to their skills.
Programmers moving into machine learning.
Anyone willing to practise maths and code regularly.
Data Science course in Hyderabad: your questions
Not here? Ask us on WhatsApp or talk to SMALL i.
Do I need coding experience?
No. Python is taught from the basics, with plenty of practice.
Do I need strong maths?
You need school-level maths to begin. The course builds the linear algebra, probability and statistics you need along the way.
How is this different from data analytics?
Analytics explains what happened using reports and dashboards. Data science goes further and builds models that predict or automate decisions.
Do I have to learn deep learning?
Deep learning is part of the syllabus, introduced after machine learning basics, so you can go as deep as you like.
Will I get a job after the course?
No institute can promise a job. Your projects, practice and interview preparation make the difference, and we help with all three.
Ready to start learning Data Science?
Meet our trainer in a free live demo, or ask SMALL i your questions first.