In today’s technology-driven world, Data Science has emerged as a crucial skill set across industries. From IT to healthcare, retail to banking, companies are seeking data-savvy professionals who can interpret complex data, derive insights, and drive strategic decisions. If you are in Hyderabad and want to build a successful career in this dynamic domain, choosing the best Data Science course in Hyderabad is the first step.
At Online IT Guru, we offer an industry-aligned Data Science Course in Hyderabad designed for freshers, working professionals, and anyone passionate about data. Our course not only teaches concepts but also ensures practical, hands-on exposure to real-world scenarios.
Why Choose Data Science as a Career in Hyderabad?
Hyderabad, being one of India’s top IT hubs, offers ample opportunities for data professionals. Here’s why a Data Science Course in Hyderabad is a smart choice:
- Booming Job Market: Hyderabad houses major tech giants, MNCs, and startups actively hiring data scientists, analysts, and AI specialists.
- High Salaries: Data Science professionals in Hyderabad command premium salaries, often 30-50% higher than other IT roles.
- Diverse Industry Demand: From pharma and finance to e-commerce and manufacturing, multiple sectors seek skilled data professionals.
- Strong Learning Ecosystem: Hyderabad offers access to expert mentors, top institutes, and tech communities for networking and growth.
Overview of Our Data Science Course in Hyderabad
The Data Science Course at Online IT Guru is designed to help learners build strong foundations and advance to cutting-edge topics like Machine Learning, Artificial Intelligence, Deep Learning, and Big Data Analytics. Our training includes:
- 60+ hours of live instructor-led sessions
- 35+ assignments for skill reinforcement
- 2 real-time projects on industry-relevant datasets
- Lifetime access to recorded sessions and materials
- Certification guidance
- Placement assistance with top companies in Hyderabad and across India
Key Highlights of the Data Science Course
- Real-Time Projects: Work on actual datasets from domains like e-commerce, healthcare, and finance.
- Hands-On Learning: Assignments, coding exercises, and case studies at the end of each module.
- Expert Trainers: Learn from professionals with 10+ years of experience in Data Science and AI.
- Flexible Schedules: Weekday, weekend, and self-paced learning options to suit your availability.
- Job Assistance: Resume building, interview preparation, and referrals to hiring partners.
Who Should Take This Data Science Course?
Our Data Science Course in Hyderabad is ideal for:
- Fresh graduates (BTech, BSc, BCA, MCA) looking to start a career in Data Science.
- Working professionals from IT, analytics, business intelligence, software development, or statistics backgrounds.
- Managers and team leads who want to leverage data for business decision-making.
- Entrepreneurs aiming to use data for scaling businesses.
- Anyone passionate about data and machine learning.
Data Science Course Eligibility and Prerequisites
There is no strict eligibility criteria. However, having basic knowledge of:
- Mathematics (statistics, probability, algebra)
- Programming fundamentals (Python preferred)
- is beneficial. Our Data Science Course covers these essentials in the foundation modules.
Detailed Syllabus of Our Data Science Course
Our best Data Science Course in Hyderabad curriculum is crafted to match industry standards. Key modules include:
Our Data Science Course in Hyderabad is designed to help learners build expertise in every essential area of data science. This curriculum follows current industry standards and is tailored for both beginners and professionals aiming to advance their careers. Below is a detailed explanation of each module and what you can expect to gain.
Introduction to Data Science
Every journey into data science begins with understanding what the field is all about. This module introduces:
- What is Data Science?
- You’ll learn that data science is the intersection of programming, statistics, and domain expertise, aimed at extracting meaningful insights from raw data. It’s not just about code or math, but about solving problems using data.
- Applications Across Industries
- Data science powers recommendation systems at Netflix and Amazon, fraud detection in banking, predictive maintenance in manufacturing, and personalized healthcare solutions. You’ll explore these and more, seeing how data science transforms industries.
- Data Science Lifecycle
- The module explains the full process:
- Problem identification.
- Data collection.
- Data cleaning.
- Exploratory analysis.
- Modeling.
- Evaluation and deployment.
- Communicating insights.
By the end of this module, you’ll appreciate the role of data science in decision-making and innovation.
Python for Data Science
Python is the most popular language for data science due to its simplicity and vast ecosystem of libraries.
- Core Python Programming
- You’ll master the essentials:
- Data types (integers, floats, strings).
- Control structures (loops, conditionals).
- Functions for modular code.
- Error handling for writing robust scripts.
- Data Structures, Functions
- Practical work with lists, dictionaries, sets, and tuples to organize and manipulate data efficiently.
- Writing custom functions to automate tasks.
- Libraries: NumPy, Pandas
- NumPy: For numerical computations and array operations.
- Pandas: For data manipulation using Series and DataFrames.
- Exercises include filtering data, merging datasets, and summarizing information.
Python proficiency is crucial because it enables you to prototype quickly, analyze data, and implement models.
Data Import, Export, and Cleaning
Data rarely comes in a ready-to-use format. This module helps you become proficient at handling raw data.
- Handling Different File Formats
- Learn to import and export data from:
- CSV files (the most common data format).
- JSON files (for web APIs and nested data).
- SQL databases (to query structured data).
- Cleaning Missing or Inconsistent Data
- Techniques for:
- Identifying and handling missing values.
- Removing duplicates.
- Standardizing formats (dates, currencies).
- Detecting and treating outliers.
You’ll work on real datasets that reflect the messiness of actual business data, ensuring you’re prepared for workplace challenges.
Data Analysis and Visualization
Once the data is clean, it’s time to explore and interpret it.
- Descriptive Statistics
- Calculate key measures like:
- Mean, median, mode.
- Standard deviation, variance.
- Correlation between variables.
- Use these to summarize and understand data distributions.
- Visualization with Matplotlib, Seaborn, Plotly
- Matplotlib: Build fundamental charts (bar, line, scatter plots).
- Seaborn: Create statistical visualizations (heatmaps, pair plots, violin plots).
- Plotly: Develop interactive charts and dashboards ideal for business reporting.
Visualization is a critical tool for telling the story of the data and revealing patterns that numbers alone can’t convey.
Applied Statistics and Probability
Statistics is at the heart of data science. This module gives you the tools to draw reliable conclusions from data.
- Hypothesis Testing
- Design experiments and test assumptions.
- Perform t-tests, chi-square tests, ANOVA.
- Understand p-values, confidence intervals, and statistical significance.
- Correlation, Regression
- Identify relationships between variables.
- Use regression to model and predict outcomes.
- Distinguish between correlation and causation.
You’ll apply these techniques in scenarios like A/B testing for marketing or modeling sales data.
Machine Learning
Here you’ll learn how to build models that allow computers to learn from data.
- Supervised vs Unsupervised Learning
- Supervised learning: Models that predict an outcome (e.g., price, category).
- Unsupervised learning: Models that find structure in data without predefined labels (e.g., customer segments).
- Algorithms
- Linear Regression: Predict continuous outcomes.
- Decision Trees: Create easy-to-interpret models that split data by features.
- K-Nearest Neighbors (KNN): Classify new data points based on similarity to known cases.
- Support Vector Machines (SVM): Build robust classifiers with clear boundaries.
- Model Evaluation
- Use metrics like accuracy, precision, recall, F1-score, ROC-AUC.
- Understand cross-validation and how to avoid overfitting.
This module focuses on applying models to real problems, like predicting customer churn or classifying transactions as fraudulent.
Deep Learning
Deep learning powers modern breakthroughs in AI, from speech recognition to image analysis.
- Neural Networks Basics
- Understand how artificial neurons and layers work.
- Learn about activation functions, forward propagation, and backpropagation.
- TensorFlow, Keras Frameworks
- Build, train, and evaluate neural networks using these popular libraries.
- Develop models more easily using Keras’ high-level API.
- CNN, RNN Architectures
- Convolutional Neural Networks (CNN): For image classification, facial recognition.
- Recurrent Neural Networks (RNN): For sequence data like time series or natural language.
You’ll build simple models for tasks like digit recognition or text sentiment analysis, preparing you for more advanced AI projects.
Natural Language Processing (NLP)
NLP is about making sense of text data — essential in today’s world of social media, chatbots, and customer reviews.
- Text Cleaning, Tokenization
- Remove noise (punctuation, stopwords).
- Break text into tokens (words or phrases).
- Convert text to numerical format (e.g., bag-of-words, TF-IDF).
- Sentiment Analysis, Text Classification
- Build models that classify text as positive/negative or into predefined categories.
- Apply NLP to customer feedback, reviews, or support tickets.
Projects in this module may include analyzing tweets for public sentiment or classifying news articles by topic.
Big Data and MLOps Introduction
For working with large-scale datasets and deploying models into production.
- Hadoop Basics
- Learn about distributed file systems (HDFS).
- Understand the MapReduce model for processing big data.
- Introduction to Model Deployment
- Learn the basics of MLOps — getting machine learning models from your notebook into production systems.
- Explore APIs, cloud deployment basics, and model monitoring.
This module ensures that learners can not only build models but also make them usable in real-world applications.
Capstone Project
The final piece of your learning journey is a real-world, end-to-end data science project.
- Apply all your skills
- Define a business problem.
- Collect and clean data.
- Analyze and visualize data.
- Build, tune, and evaluate models.
- Present your findings through reports or dashboards.
Examples:
Predicting sales for a retail chain.
Building a movie recommendation system.
Detecting fraudulent transactions.
The capstone helps build your portfolio, Data Science Course demonstrating your ability to solve data science problems from start to finish — a key asset for job interviews.
Projects Covered
- Customer churn prediction for a telecom company
- Sales forecasting for a retail store
- Sentiment analysis of social media data
- Healthcare analytics for patient readmission prediction
Training Options for Data Science Course
We offer:
- Live online training
- Self-paced learning with recorded sessions
- Corporate training with customized curriculum
Data Science Course Fees in Hyderabad
At Online IT Guru, we believe in offering value for money:
- Standard fee: ₹35,000
- Discounted fee: ₹16,280 (Limited period offer)
- EMI options available
Placement Support
Our dedicated placement cell:
- Helps with resume and LinkedIn profile building
- Conducts mock interviews
- Connects you with hiring partners (200+ companies)
Top hiring industries: IT, banking, healthcare, telecom, e-commerce, Online IT Guru retail.
Benefits of Choosing Online IT Guru for Your Data Science Course
- Trusted by 8600+ learners
- 4.9/5 rating by students
- Real-world case studies integrated in learning
- Lifetime LMS access
- 24x7 learner support
10 Frequently Asked Questions
1. What is the duration of the Data Science Course in Hyderabad?
The course is 60+ hours of instructor-led training, usually completed in 2-3 months depending on batch type.
2. Do I need prior coding experience to join?
No prior coding is mandatory. We cover Python from basics.
3. Will I get placement assistance after the course?
Yes. We offer resume support, interview prep, and connect learners with hiring partners.
4. Can I pay the fees in installments?
Yes, we offer EMI options for easier payment.
5. What certificate will I get after completing the course?
You’ll receive a Data Science course completion certificate from Online IT Guru.
6. Are there weekend batches available?
Yes, we offer both weekday and weekend options.
7. Will I work on live projects?
Yes. The course includes 2 real-time projects on industry-relevant problems.
8. What if I miss a session?
You’ll have access to class recordings and can also attend a repeat session.
9. How is this course different from others in Hyderabad?
Our course offers a practical, project-driven approach with personalized support, job assistance, and lifetime access.
10. Can I get a free trial before enrolling?
Yes. We offer a free demo session so you can experience the learning style.