Data Science Course in Chennai
Join our 3-months Data Science Course in Chennai, structured for recent graduates, final-year students, and programmers ready to shift careers. This intensive program combines theory and hands-on practice to prepare you for entry-level data science roles. Through self-paced modules and live sessions, you will learn core skills, covering Excel, Power BI, Python programming, and essential math concepts. Build industry-ready expertise and confidently enter data science with this comprehensive training.
If you’re looking to break into the field of data science, the Hyper Launch Data Science Course in Chennai is designed to equip you with in-demand skills and real-world experience. Hyper Launch’s course covers everything you need to excel—from foundational topics like statistics and data manipulation to advanced techniques in machine learning, big data, and AI. With hands-on practice in tools like Python, SQL, TensorFlow, Powe BI and Spark, you’ll gain the practical expertise needed to thrive in today’s data-driven industries.
Chennai is one of India’s booming tech hubs, and companies across sectors are actively seeking skilled data professionals. Hyper Launch’s curriculum not only prepares you for a high-demand role but also offers insights tailored to Chennai’s local job market. Whether you’re interested in business analytics, data engineering, or AI development, the Hyper Launch Data Science Course ensures you’re ready to meet industry needs.
Hyper Launch’s Course also offers placement support to help you start or advance your career, whether you’re aiming for a data analyst, data scientist, or business intelligence role. In Chennai, data scientist salaries start around ₹5-8 lakhs annually for beginners, with the potential for seasoned professionals to earn ₹15 lakhs or more. With Hyper Launch, you’ll be learning from top instructors and gaining the skills that matter most. Take the next step in your career with the Hyper Launch Data Science Course in Chennai —your future in data science awaits.
Why Hyper Launch Data Science Course
The Hyper Launch Data Science Course in Chennai goes beyond traditional teaching methods by incorporating mentorship and personalized guidance, ensuring students not only understand the concepts but can apply them confidently in real-world scenarios. This course includes career-building resources such as mock interviews, resume workshops, and one-on-one mentoring sessions that help bridge the gap between learning and professional success. Additionally, Hyper Launch maintains a strong network of industry partnerships with top companies in Chennai’s IT, finance, and retail sectors, giving students access to exclusive internship and job placement opportunities.
Another feature that sets Hyper Launch apart is its flexible learning options, allowing both online and hybrid formats to suit the needs of working professionals and recent graduates alike. Students can learn at their own pace, supported by regular assessments and feedback from experienced data science professionals. Hyper Launch’s dedicated support doesn’t end at course completion; they offer ongoing career guidance to alumni, ensuring that graduates stay updated with industry trends and continue advancing their careers in data science.
Learning Objectives
- Learn core concepts of data science and explore its applications
- Understand the role of data in improving decision-making
- Apply mathematical and statistical techniques for data analysis
- Use Microsoft Excel and Power BI to visualize and analyze data effectively
- Implement Python for data manipulation and machine learning tasks
- Analyze datasets to extract valuable insights and conclusions
- Assess the accuracy and effectiveness of machine learning models
- Create clear, data-driven reports and visualizations
- Build problem-solving and critical-thinking skills through data projects
Course Duration
Total
Duration
12 Weeks (3 Months)
3 Weeks Placement Readiness
Weekly
Commitment
10-12 Hours
Pre-Requisites
Basic Computer Literacy
Familiarity with operating systems, file management, and basic software installation.
Mathematics Basics
Understanding of high school-level mathematics.
Basic Programming Knowledge (Preferred)
Familiarity with any programming language (preferable but not mandatory).
Course Outline
Introduction to Data Science
Day 1: Overview of Data Science (Live Class, 90 mins)
- Video: Introduction to Data Science
- Reading Material: Overview of Data Science
- Quiz: Basics of Data Science
Day 2: Data Collection Methods (Live Class, 90 mins)
- Reading Material: Data Sources and Collection
- Practical Assignment: Collecting Data from APIs
Day 3: Data Cleaning and Preprocessing (Live Class, 90 mins)
- Video: Data Cleaning Techniques
- Practical Assignment: Cleaning a Dataset in Excel
Day 4: Introduction to Python for Data Science (Live Class, 90 mins)
- Reading Material: Python Basics
- Practical Assignment: Writing Basic Python Scripts
Day 5: Data Types and Data Structures in Python (Live Class, 90 mins)
- Video: Python Data Structures
- Quiz: Python Basics
Excel for Data Analysis
Day 1: Excel Basics for Data Analysis (Live Class, 90 mins)
- Reading Material: Excel Fundamentals
- Practical Assignment: Basic Excel Functions
Day 2: Data Cleaning in Excel (Live Class, 90 mins)
- Video: Excel Data Cleaning Techniques
- Practical Assignment: Cleaning a Dataset in Excel
Day 3: Data Analysis with Excel (Live Class, 90 mins)
- Reading Material: Excel Data Analysis Tools
- Practical Assignment: Analyzing a Dataset in Excel
Day 4: Advanced Excel Functions (Live Class, 90 mins)
- Video: Advanced Excel Techniques
- Quiz: Excel Functions
Day 5: Excel Dashboarding (Live Class, 90 mins)
- Reading Material: Creating Dashboards in Excel
- Practical Assignment: Building an Excel Dashboard
Data Visualization with power BI
Day 1: Introduction to Power BI (Live Class, 90 mins)
- Video: Getting Started with Power BI
- Reading Material: Power BI Basics
Day 2: Connecting and Transforming Data in Power BI (Live Class, 90 mins)
- Practical Assignment: Data Connections in Power BI
Day 3: Creating Visualizations in Power BI (Live Class, 90 mins)
- Video: Visualization Techniques in Power BI
- Practical Assignment: Building Power BI Reports
Day 4: Advanced Power BI Features (Live Class, 90 mins)
- Reading Material: Advanced Power BI
- Quiz: Power BI Features
Day 5: Power BI Dashboards (Live Class, 90 mins)
- Practical Assignment: Creating Interactive Dashboards in Power BI
Data Analysis with Python
Day 1: Introduction to Pandas (Live Class, 90 mins)
- Video: Getting Started with Pandas
- Reading Material: Pandas Basics
Day 2: Data Cleaning with Pandas (Live Class, 90 mins)
- Practical Assignment: Cleaning Data with Pandas
Day 3: Data Manipulation with Pandas (Live Class, 90 mins)
- Reading Material: Advanced Pandas
- Practical Assignment: Data Transformation with Pandas
Day 4: Data Analysis with Pandas (Live Class, 90 mins)
- Video: Analyzing Data with Pandas
- Practical Assignment: Performing EDA with Pandas
Day 5: Data Visualization with Matplotlib (Live Class, 90 mins)
- Practical Assignment: Creating Plots with Matplotlib
Statistics for Data Science
Day 1: Introduction to Statistics (Live Class, 90 mins)
- Reading Material: Basic Statistical Concepts
- Quiz: Basic Statistics
Day 2: Descriptive Statistics (Live Class, 90 mins)
- Video: Descriptive Statistics Techniques
- Practical Assignment: Descriptive Analysis in Python
Day 3: Inferential Statistics (Live Class, 90 mins)
- Reading Material: Inferential Statistics Concepts
- Practical Assignment: Hypothesis Testing in Python
Day 4: Probability Theory (Live Class, 90 mins)
- Video: Introduction to Probability
- Quiz: Probability Concepts
Day 5: Statistics with Python (Live Class, 90 mins)
- Practical Assignment: Statistical Analysis with Python
Exploratory Data Analysis (EDA)
Day 1: EDA Overview (Live Class, 90 mins)
- Video: EDA Techniques
- Reading Material: Importance of EDA
Day 2: Data Visualization for EDA (Live Class, 90 mins)
- Practical Assignment: Visualizing Data for EDA
Day 3: Summary Statistics and Data Distributions (Live Class, 90 mins)
- Reading Material: Data Distributions
- Practical Assignment: Calculating Summary Statistics
Day 4: Identifying Patterns and Outliers (Live Class, 90 mins)
- Video: Detecting Outliers
- Practical Assignment: Analyzing Patterns in Data
Day 5: EDA Project (Live Class, 90 mins)
- Practical Assignment: EDA on a Real Dataset
Introduction to Machine Learning
Day 1: Machine Learning Basics (Live Class, 90 mins)
- Reading Material: Introduction to Machine Learning
- Quiz: Machine Learning Concepts
Day 2: Supervised Learning – Regression (Live Class, 90 mins)
- Practical Assignment: Implementing Linear Regression
Day 3: Supervised Learning – Classification (Live Class, 90 mins)
- Video: Classification Techniques
- Practical Assignment: Implementing Logistic Regression
Day 4: Unsupervised Learning – Clustering (Live Class, 90 mins)
- Practical Assignment: Implementing K-Means Clustering
Day 5: Model Evaluation and Validation (Live Class, 90 mins)
- Reading Material: Model Evaluation Techniques
- Quiz: Model Evaluation
Advanced Machine Learning
Day 1: Decision Trees and Random Forests (Live Class, 90 mins)
- Video: Tree-Based Methods
- Practical Assignment: Implementing Decision Trees
Day 2: Ensemble Methods (Live Class, 90 mins)
- Reading Material: Ensemble Techniques
- Practical Assignment: Implementing Random Forests
Day 3: Support Vector Machines (Live Class, 90 mins)
- Practical Assignment: Implementing SVM
Day 4: Neural Networks Introduction (Live Class, 90 mins)
- Video: Basics of Neural Networks
- Quiz: Neural Networks Concepts
Day 5: Model Tuning and Optimization (Live Class, 90 mins)
- Practical Assignment: Hyperparameter Tuning
Big Data Technologies
Day 1: Introduction to Big Data (Live Class, 90 mins)
- Reading Material: Big Data Concepts
- Quiz: Big Data Basics
Day 2: Working with Hadoop (Live Class, 90 mins)
- Video: Hadoop Ecosystem
- Practical Assignment: Introduction to Hadoop
Day 3: Introduction to Spark (Live Class, 90 mins)
- Practical Assignment: Working with Spark
Day 4: SQL for Data Science (Live Class, 90 mins)
- Reading Material: SQL Basics
- Practical Assignment: Writing SQL Queries
Day 5: Integrating Big Data Tools (Live Class, 90 mins)
- Practical Assignment: Big Data Project
Real-World Data Science Applications
Day 1: Case Studies in Data Science (Live Class, 90 mins)
- Video: Successful Data Science Projects
- Reading Material: Data Science Case Studies
Day 2: Industry-Specific Data Science Applications (Live Class, 90 mins)
- Practical Assignment: Analyzing Industry Data
Day 3: Ethics in Data Science (Live Class, 90 mins)
- Reading Material: Data Ethics
- Quiz: Ethical Considerations in Data Science
Day 4: Data Science for Social Good (Live Class, 90 mins)
- Practical Assignment: Social Good Project
Day 5: Capstone Project Planning (Live Class, 90 mins)
- Practical Assignment: Project Proposal
Capstone Project Development
Day 1: Project Development – Data Collection (Live Class, 90 mins)
- Practical Assignment: Collecting Project Data
Day 2: Project Development – Data Cleaning (Live Class, 90 mins)
- Practical Assignment: Cleaning Project Data
Day 3: Project Development – Data Analysis (Live Class, 90 mins)
- Practical Assignment: Analyzing Project Data
Day 4: Project Development – Visualization (Live Class, 90 mins)
- Practical Assignment: Visualizing Project Data
Day 5: Project Development – Modeling (Live Class, 90 mins)
- Practical Assignment: Building Project Models
Capstone Project and Review
Day 1: Finalizing Capstone Project (Live Class, 90 mins)
- Practical Assignment: Finalizing Project Report
Day 2: Preparing for Presentation (Live Class, 90 mins)
- Practical Assignment: Creating Presentation Slides
Day 3: Presentation Skills Workshop (Live Class, 90 mins)
- Video: Effective Presentation Techniques
- Practical Assignment: Practicing Presentation
Day 4: Capstone Project Presentation (Live Class, 90 mins)
- Practical Assignment: Presenting Capstone Project
Day 5: Review and Feedback (Live Class, 90 mins)
- Practical Assignment: Incorporating Feedback
- Reading Material: Reflective Analysis
Data Science Course Outline Chart
Frequently Asked Questions
What does Hyper Launch’s data science course cover?
Hyper Launch’s course covers all major aspects of data science, from foundational skills in statistics to advanced machine learning, with hands-on training on real projects.Why choose Hyper Launch for a data science course in Chennai?
Hyper Launch is known for industry-aligned curriculum and career-oriented training, helping students gain in-demand skills and hands-on experience for the Chennai job market.Is prior experience needed to join Hyper Launch’s data science course?
No prior experience is necessary. The course is designed for beginners and professionals, starting from basics and advancing to expert-level knowledge.What programming languages are taught in this course?
The course covers essential languages like Python, which are crucial for data analysis, machine learning, and data visualization.Will I receive a certification from Hyper Launch?
Yes, upon completing the course, students receive a certification that is recognized by employers and adds value to your resume.How long is the Hyper Launch data science course?
The course duration is flexible, with options for part-time or full-time learning paths. Typically, it spans a few months depending on the learning pace.Does Hyper Launch offer job placement support?
Yes, Hyper Launch provides robust placement assistance, connecting students with leading employers in Chennai’s data science industry.Is there a demo class before enrolling?
Yes, prospective students can attend a demo class to experience Hyper Launch’s teaching approach and course structure before committing.How is Hyper Launch’s data science course structured?
The course combines lectures, hands-on labs, and industry projects, ensuring practical knowledge that translates into real-world skills.What career outcomes can I expect from this course?
Graduates can pursue roles like data analyst, data scientist, or machine learning engineer, with Hyper Launch’s dedicated support in career placement.Are there flexible payment options?
Hyper Launch offers various payment plans to make the course affordable, including installment options and potential scholarships.What industries does this course prepare me for?
Hyper Launch’s curriculum prepares students for roles in tech, finance, healthcare, retail, and more, where data science skills are in high demand.How is Hyper Launch’s curriculum designed?
The curriculum is crafted by industry experts to ensure students learn current, relevant skills that match industry expectations.What kind of projects will I work on in this course?
Students work on real-world projects, including predictive modeling, data analysis, and machine learning applications, to build a strong portfolio.How can I enroll in the Hyper Launch data science course?
Enrolling is easy—visit the Hyper Launch website, contact the admissions team, or attend a demo session to get started.