Data Science Course in Bangalore

Data Science Course in Bangalore designed to help students, fresh graduates and working professionals develop practical skills in Python, data analysis, statistics, machine learning, artificial intelligence and data visualization.

The programme takes learners through the complete data science workflow, starting with programming and data fundamentals and progressing into exploratory data analysis, machine learning, artificial intelligence, model development and practical projects.

Through structured learning and hands-on assignments, learners can develop the technical foundation required to work with real-world datasets, identify patterns, build predictive models and communicate data-driven insights.

Course Overview

Data science combines programming, statistics, mathematics, data analysis and machine learning to solve practical problems using data. Modern organizations use data science to understand customers, forecast trends, automate processes and support business decisions.

This programme provides a structured pathway from Python and data analysis fundamentals to machine learning and artificial intelligence. Learners progressively build their knowledge through practical exercises, projects and portfolio development.

With its combination of programming, analytics and machine learning, the Data Science Course in Bangalore provides learners with a structured foundation for exploring careers in data science, machine learning and artificial intelligence.

Course Details

• Course: Data Science & Artificial Intelligence
• Duration: 6 Months
• Learning Path: Beginner → Intermediate → Advanced
• Programming: Python
• Data Tools: Python Libraries, SQL and Data Visualization Tools
• Core Areas: Data Analysis, Statistics, Machine Learning and Artificial Intelligence
• Projects: Practical Data Science Projects
• Internship: Included
• Certification: Included
• Career Support: Placement Assistance and Career Preparation

Why Learn Data Science?

Organizations increasingly rely on data to understand customers, improve operations, identify opportunities and make informed decisions. Data science brings together programming, statistics and machine learning to extract useful information from large and complex datasets.

Learning data science can help students develop skills across several technical areas, including Python programming, data preparation, exploratory data analysis, visualization, machine learning and artificial intelligence.

The Data Science Course in Bangalore focuses on building these skills progressively so that learners can move from programming fundamentals to practical data science applications.

What Will You Learn?

Python Programming for Data Science

• Python Fundamentals
• Variables and Data Types
• Operators and Expressions
• Conditional Statements
• Loops
• Functions
• Lists, Tuples, Sets and Dictionaries
• File Handling
• Object-Oriented Programming
• Python Libraries

Data Analysis with Python

• Data Loading
• Data Cleaning
• Data Transformation
• Data Preparation
• Exploratory Data Analysis
• Working with Structured Datasets
• Data Aggregation
• Data Visualization
• Insight Generation

SQL and Database Concepts

• Database Fundamentals
• SQL Basics
• SELECT Queries
• Filtering and Sorting
• Aggregate Functions
• GROUP BY and HAVING
• Joins
• Subqueries
• Data Retrieval

Statistics for Data Science

• Descriptive Statistics
• Mean, Median and Mode
• Variance and Standard Deviation
• Probability Fundamentals
• Distributions
• Correlation
• Statistical Analysis
• Data Interpretation

Machine Learning

• Introduction to Machine Learning
• Supervised Learning
• Unsupervised Learning
• Regression
• Classification
• Clustering
• Feature Engineering
• Model Evaluation
• Training and Testing Data
• Machine Learning Projects

Artificial Intelligence

• Introduction to Artificial Intelligence
• AI Fundamentals
• Machine Learning Applications
• Neural Network Fundamentals
• AI Applications
• Generative AI Fundamentals
• AI-Assisted Development
• Practical AI Projects

The practical structure of this Data Science Course in Bangalore allows learners to connect Python programming, data analysis, statistics, machine learning and artificial intelligence through practical exercises and projects.

This Data Science Course in Bangalore combines programming, data analysis, statistics, machine learning and artificial intelligence to give learners a practical foundation in modern data science.

Data Visualization

Data visualization helps transform analytical results into information that can be understood and communicated effectively.

• Charts and Graphs
• Exploratory Visualizations
• Data Storytelling
• Dashboard Fundamentals
• Business Data Visualization
• Communicating Analytical Insights

Machine Learning Workflow

Learners are introduced to the major stages involved in developing machine learning solutions.

1. Understanding the problem
2. Collecting and preparing data
3. Cleaning datasets
4. Exploratory data analysis
5. Feature preparation
6. Training machine learning models
7. Evaluating model performance
8. Improving model performance
9. Interpreting results

Who Should Enroll?

Students

• MCA Students
• BCA Students
• B.Tech and BE Students
• B.Sc Students
• Computer Science Students
• Engineering Students

Fresh Graduates

Fresh graduates who want to develop practical programming, analytics and machine learning skills can use the programme to build a technical foundation and portfolio.

Working Professionals

Working professionals who want to expand their technical knowledge or transition toward data-focused roles can develop practical skills in Python, analytics and machine learning.

Career Switchers

Learners from non-technical backgrounds who are interested in developing programming and data skills can start with the fundamentals and progress toward advanced concepts.

Aspiring Data Scientists

Learners interested in data science, machine learning and artificial intelligence can use the programme to build practical knowledge through projects and assignments.

Course Curriculum

Beginner Level

• Introduction to Data Science
• Python Programming Fundamentals
• Programming Logic
• Python Data Structures
• Functions and Modules
• Object-Oriented Programming
• Introduction to Data Analysis
• Beginner Python Project

Intermediate Level

• Python for Data Analysis
• Data Cleaning
• Exploratory Data Analysis
• SQL
• Statistics
• Data Visualization
• Feature Engineering
• Intermediate Data Science Project

Advanced Level

• Machine Learning
• Regression
• Classification
• Clustering
• Model Evaluation
• Artificial Intelligence
• Neural Network Fundamentals
• Generative AI Fundamentals
• Advanced Data Science Project

Practical Data Science Projects

Project-based learning gives students an opportunity to apply programming, analytics and machine learning concepts to practical problems.

• Python programming project
• Data cleaning project
• Exploratory data analysis project
• SQL analytics project
• Data visualization project
• Statistical analysis project
• Regression project
• Classification project
• Clustering project
• Machine learning project
• Artificial intelligence project
• Generative AI project
• Final data science capstone project

These projects are designed to help learners practice the complete workflow from understanding a problem and preparing data to analyzing results and presenting their findings.

Build Your Data Science Portfolio

A practical portfolio can help demonstrate technical skills beyond a course certificate. Learners can use their completed projects to showcase Python programming, data analysis, visualization, machine learning and AI capabilities.

Projects can be documented through GitHub repositories, project reports and portfolio presentations to demonstrate the development process and final results.

Through project-based learning, the Data Science Course in Bangalore helps learners develop a portfolio that demonstrates their ability to work with data and build practical machine learning solutions.

Artificial Intelligence and Generative AI

Artificial intelligence is an important part of modern data-driven applications. The programme introduces learners to AI concepts and practical applications while building a foundation in machine learning.

Learners can also explore how generative AI tools can support programming, data analysis, documentation and productivity workflows.

Internship and Practical Experience

The programme includes an internship component designed to provide additional practical exposure. Internship tasks can help learners reinforce concepts covered during training and gain experience working through structured project requirements.

The combination of training, projects and internship experience can help learners develop a stronger practical portfolio for data-focused career opportunities.

Career Preparation

Technical training is supported by career preparation activities designed to help learners present their skills and prepare for recruitment processes.

• Resume Building
• LinkedIn Profile Optimization
• GitHub Portfolio Development
• Technical Interview Preparation
• Project Presentation
• Mock Interviews
• Career Guidance

Career Opportunities

After developing practical skills in programming, analytics and machine learning, learners can explore roles such as:

• Data Scientist
• Junior Data Scientist
• Data Analyst
• Machine Learning Engineer
• AI Engineer
• Machine Learning Developer
• Business Intelligence Analyst
• Data Science Intern
• AI/ML Intern
• Python Developer

Learning Resources

• Python Learning Materials
• SQL Practice Exercises
• Data Analysis Exercises
• Machine Learning Assignments
• AI Learning Materials
• Project Resources
• Practice Datasets
• Assessments
• Internship Tasks
• Career Preparation Resources

Official Data Science and AI Resources

Learners can continue developing their technical knowledge through official documentation and learning resources from the technologies used in data science and machine learning.

• Python Documentation
  – Official Python documentation and language reference.
• Pandas Documentation
  – Official documentation for data manipulation and analysis with Pandas.
• Scikit-learn User Guide
  – Official documentation for machine learning algorithms and workflows.
• TensorFlow Learning Resources
  – Official TensorFlow tutorials and learning resources for machine learning.

Explore Other Technology Courses

If you are interested in developing additional technology skills alongside data science and AI, explore other career-focused programmes from Scholar’sEdge Academy.

• 
  Data Analytics & Business Intelligence Course in Bangalore
  
  – Learn data analytics, SQL, Power BI, Tableau and business intelligence.
• 
  Full Stack Development Course in Bangalore
  
  – Learn frontend, backend, APIs, databases and full-stack development.
• 
  Mobile App Development Course in Bangalore
  
  – Learn mobile application development, Flutter, APIs and modern app technologies.
• 
  Digital Marketing Course in Bangalore
  
  – Develop practical skills in SEO, advertising, analytics and digital marketing.

The Data Science Course in Bangalore also gives learners opportunities to apply their knowledge through practical assignments, projects and portfolio development.

Start Your Data Science Journey

Develop practical skills in Python, SQL, data analysis, statistics, machine learning and artificial intelligence through structured learning and hands-on projects.

Whether you are a student, fresh graduate, working professional or career switcher, this programme provides a structured pathway from programming fundamentals to advanced data science and AI concepts.

The Data Science Course in Bangalore is designed to help learners build technical knowledge, complete practical projects, develop a portfolio and prepare for data-focused career opportunities.

Start learning data science and build practical skills for the data-driven technology industry.