Data Science & Analytics Course in Chennai
825 Ratings
Build a future-ready career in data-driven technologies with Edubrights' Data Science & Analytics Course in Chennai. Designed for students, freshers, job seekers, and working professionals, this training program helps you develop practical skills in data analysis, statistical modeling, predictive analytics, and business intelligence through hands-on learning and real-world projects.
Learn how organizations leverage data science and analytics to uncover insights, optimize business performance, forecast trends, and make informed decisions. Through industry-focused assignments, practical case studies, and project-based training, you will gain the expertise needed to solve complex business challenges using data-driven approaches.
Key Highlights:
✅ Real-Time Data Science & Analytics Projects and Industry Case Studies
✅ Hands-On Training in Data Analysis, Statistical Modeling, and Predictive Analytics
✅ Data Visualization, Reporting, and Business Intelligence Concepts
✅ Practical Exposure to Data-Driven Decision-Making and Problem Solving
✅ Industry-Aligned Curriculum Designed by Experienced Data Professionals
✅ Certification Guidance and Career Development Support
✅ Resume Building, Mock Interviews, and Placement Assistance
✅ Flexible Online, Classroom, and Weekend Training Options
Start your Data Science & Analytics journey with Edubrights and gain the practical skills, project experience, and industry knowledge needed to become a job-ready data professional in today's data-driven business environment.
Call Course Advisor
₹30000
₹45000
Case Studies and Projects
2+
Hours of Training
20+
Placement Assurance
100%
Expert Support
Yes
Support & Access
Lifetime
Certification
Yes
Skill Level
All
Language
All
Course Objectives
1. What exactly Data Science & Analytics training cover?
The training covers data collection, cleaning, visualization, statistical modeling, machine learning, and big data technologies to extract valuable insights from complex datasets.
2. What are the main objectives of the Data Science & Analytics course for your development skills?
To develop practical skills in data analysis, predictive modeling, data visualization, and decision-making that drive business solutions.
3. Which technologies are used in Data Science & Analytics?
Explore Python, SQL, Pandas, NumPy, Matplotlib, Power BI, Tableau, Scikit-learn, TensorFlow, Jupyter Notebook, and cloud-based analytics platforms.
4. How does Data Science improve business intelligence and predictive analytics?
Learn how data cleaning, visualization, machine learning models, and statistical analysis help organizations forecast trends and solve real-world business challenges.
Popular Techniques Covered in This Course
1.Data preprocessing and cleaning
2.Statistical modeling
3.Machine learning algorithms
4.Data visualization and dashboarding
5.Big data tools (Hadoop, Spark)
6.Python and R programming
7.Natural Language Processing (NLP)
8.Time series analysis
9.Data mining techniques
10.Data ethics and governance
Get Hands-on Knowledge about Real-Time Projects
Project 1
1. Customer Churn Prediction
Analyze customer data to predict churn and suggest retention strategies.
Project 2
2. Sales Data Dashboard
Develop interactive dashboards to visualize sales trends and KPIs.
Project 3
3. Financial Risk Analysis & Credit Default Predictor
Construct a binary classification model designed to assess applicant risk profile data. By balancing historical loan variables and deploying logistic regression frameworks, your script will compute specific probability scores indicating potential future credit defaults.
Project 4
4. Digital Marketing Campaign A/B Testing Engine
Analyze real-world web traffic logs to determine the statistical performance of parallel marketing assets. You will perform data cleaning, compute confidence intervals, and execute rigorous hypothesis testing to confirm whether design variations caused a definitive lift in conversion rates
Project 5
5. Multi-Store Retail Sales Forecasting System
Build an enterprise-grade time-series forecasting model that projects monthly product demand across dozens of distinct inventory categories. You will merge historical sales numbers with localized seasonal trends to generate highly accurate stock level recommendations.
Key Features
Edubrights offers Data Science & Analytics Training in virtual mode with expert trainers. Here are the key features.
40 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance
Curriculum
Module 1: Data Fundamentals
- Data types, collection methods
- Cleaning and preprocessing data
- Exploratory Data Analysis (EDA)
Module 2: Programming for Data Science
- Python and R basics
- Libraries: Pandas, NumPy, Matplotlib, Seaborn
Module 3: Statistics & Probability
- Descriptive and inferential statistics
- Hypothesis testing
- Probability distributions
Module 4: Data Visualization
- Creating charts and dashboards
- Tools: Tableau, Power BI, Matplotlib
Module 5: Machine Learning Basics
- Supervised and unsupervised learning
- Regression, classification, clustering
Module 6: Big Data Tools
- Introduction to Hadoop, Spark
- Data storage and processing
Module 7: Advanced Analytics
- Time series analysis
- Natural Language Processing (NLP)
Module 8: Capstone Project & Ethics
- Real-world data project
- Data ethics and privacy
Receive Training From Our Skilled and Effective Trainers
Experience in the Industry Gain knowledge from experts with practical Data Science & Analytics project experience in a variety of sectors.
Backgrounds at the Top Prominent corporations such as HCL, TCS, Accenture, and Cognizant employ trainers.
Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.
Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.
Up-to-Date Knowledge Trainers stay current with the latest tools, techniques, and best practices.
Succeed Our Resourceful Certification
Our certification highlights your ability to analyze complex datasets, build predictive models, and deliver actionable insights. It prepares you for diverse roles in data-driven industries.
Course FAQs
1. What is data science?
Data science involves analyzing and interpreting complex data to help make informed decisions.
2. Do I need programming knowledge?
Basic programming in Python or R is recommended.
3. What jobs can I get?
Data analyst, data scientist, business analyst, machine learning engineer.
4. Will I do hands-on projects?
Yes, practical projects and case studies are integral.
5. How long does the course last?
Typically 4–6 months depending on the program.
6. Is math important?
Yes, statistics and probability are essential.
7. What tools will I use?
Python, R, Tableau, Power BI, Hadoop, Spark.
8. Does the course cover big data?
Yes, introduction to big data technologies is included.
9. Can I pursue higher studies afterwards?
Yes, data science opens pathways to AI, analytics, and research.
10. How to stay updated?
Follow research, attend webinars, and participate in competitions.
11. Is there a heavy emphasis on data storytelling?
Absolutely. Cleaning data is only half the battle. A massive component of our curriculum focuses on translating raw numbers into clear business recommendations, teaching you how to present findings to non-technical managers and executive boards.
12. Can I transition directly into a Data Analyst role after this course?
Yes. The course is precisely mapped to match global job descriptions for Data Analysts, Business Intelligence (BI) Analysts, and Junior Data Scientists, ensuring your portfolio showcases the exact skills hiring teams look for.
13. Are the course modules updated for current 2026 industry standards?
Yes. The entire curriculum undergoes consistent optimization via our panel of industry experts, ensuring outdated methodologies are replaced with modern MLOps practices, advanced DAX formulas, and current data governance models.
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