Ultimate Guide to Data Science Courses in Bangalore

Bangalore – India’s tech capital – offers a vibrant ecosystem for data science education and careers. The city  leads with 25% of India’s data science job openings and is projected to see 50% growth in DS roles by 2027 . Renowned for its IT hubs, start-ups and research institutions, Bangalore attracts top-tier DS programs. In this guide, we list the top 20 Data Science courses in Bangalore (2025) – covering institute name, location (area and pin code), nearby landmarks/metro, and key course details (duration, mode, fees, eligibility) – followed by industry trends, tools overview, syllabus summary, mentorship, FAQs and more. Each section is clearly organized for easy reading.  

Why Choose Bangalore for Data Science? 

•  Industry Hub: Bangalore houses major tech companies (Infosys, Wipro, Flipkart, etc.), leading analytics firms, and AI labs. Its flourishing start-up scene and R&D centers mean ample data science opportunities and collaborations.

•  Job Market: The city accounts for over a quarter of India’s DS jobs . With 10,000+ active DS 2 vacancies currently (LinkedIn/Naukri) , demand continues to grow. Tech trends (AI, Big Data, IoT) further fuel hiring in Bangalore.

•  Academic & Training Excellence: Top universities (IISc, IIIT-B), institutes (IIIT, IIM-B), and numerous private academies (Skillfloor, Great Learning, AnalytixLabs, etc.) offer cutting-edge curriculum and industry projects. Experienced mentors and instructor-led workshops are readily available.

•  Networking and Mentors: Data science meetups, hackathons and seminars are routine. You’ll find industry experts like Amit Agarwal (NVIDIA), Anish Agarwal (RBC) and Ashish Thusoo (ex Facebook) mentoring students . This community gives learners a clear learning path and career guidance.

•  Salary Prospects: Bangalore DS professionals earn competitive pay. Entry-level Data Scientists typically make ~₹6–12 LPA, mid-career ₹15–25 LPA, and senior roles ₹30–50+ LPA . Data Analysts earn roughly ₹3.5–14 LPA with experience . (ML engineers and AI specialists can command up  to ₹70 LPA .) 

Top 20 Data Science Courses in Bangalore (2025)

1. Skillfloor - Room no.3 2nd floor, C 25 Bajrang House, 7Th Mile, Hosur Rd, near Kudlu Gate, Bengaluru, Karnataka 560068

-Certified Data Science Professional - 2 months
-Fees: ₹14,900;   (Industry projects and 100% placement assistance.)
-Eligibility: Bachelor’s.

2. Datamites – 1st Floor, 761/1, Outer Ring Rd, near KLM Mall, Marathahalli Village, Marathahalli, Bengaluru, Karnataka 560037.

-Certified data scientist : 6 months;
-Fees: ₹80,000;
-Eligibility: Bachelor’s. (Industry projects and 100% placement assistance.) 

3. Learnbay – HSR Layout (Sector 3), Bengaluru 560102 (above Sangam Sweets; nearest Kadubeesanahalli metro).

-PG Program in DS & AI: 4–10 months (flexible batches, online/onsite);
-Fee: ~₹1.5 L
-Eligibility: Graduate (STEM) . Offers mentorship and placement assistance.

4. AnalytixLabs – HSR Layout (Sector 6), Bengaluru 560102 (opp. A2B, near BDA Complex).

-PG in Data Science & ML: 4–7 months;
-Fees: ~₹99,000 ;
-Eligibility: Any graduate. Known for hands-on labs and live projects. 

5. ExcelR Solutions – BTM Layout, Stage I, Bengaluru 560068 (Behind Tata Motors, 27th Main).

-DataScience Bootcamp: 6–12 months;
-Fees: ~₹60,000;
-Eligibility: Graduate. (Offers weekend and online options.) 

6. Simplilearn – Bommanahalli, Bengaluru 560068 (1st & 2nd Floor, IBIS Hotel, Hosur Road).

-Postgraduate Program in Data Science (Purdue University): 6 months online;
-Fees: ~₹80,000 ; 
-Eligibility: Any graduate. (Global cert on completion.) 

7. 360DigiTMG – HSR Layout (Sector 7), Bengaluru 560102.

-Data Science & AI PG Program: 6 months;
-Fees: ₹65,000+ ;
-Eligibility: Graduate. Known for industry-oriented capstone projects. 

8. Intellipaat – Bellandur, Bengaluru 560103 (74, 2nd Floor, above ICICI Bank; near Silk Institute Metro).

-Executive PG Program in DS & ML: 11 months;
-Fees: ₹1.75 L;
-Eligibility: Bachelor’s. Focus on job readiness with live enterprise projects . 

9. Besant Technologies – Jayanagar, Bengaluru 560041 (Jayanagar Metro).

-Data Science Training: 6 months;
-Fees: ₹60,000 (approx.)
-Eligibility: Any grad. (Offers flexible class schedules.) 

10. StarAgile – HSR Layout (Sector 7), Bengaluru 560102 (Opp. Gopalan Mall on 9th Main).

-PG Program in DS & AI: 6–12 months;
-Fees: ₹90,000;
-Eligibility: Graduate. Includes mentorship and placement support. 

11. Scaler (InterviewBit) – Bellandur, Bengaluru 560103 (GreenGlen Layout, 9th Floor Sakti Statesman). 

-Advanced Program in Software & Data Science: 11–13 months;
-Fees: ₹2.5 L ;
-Eligibility: Engineering grad. (Full-time on-site classes M–Th.) 

12. Apponix – Marathahalli, Bengaluru 560037 (Opp. Max Showroom, HAL Old Airport Rd).

-Data Science Bootcamp: ~3 months;
-Fees: ₹0.3–1 L;
-Eligibility: Any graduate. (Short-term crash courses with flexible options.) 

13. Imarticus Learning – Koramangala, Bengaluru 560095.

-PGP in Data Science: 6 months;
-Fees: ₹2.15 L ;
-Eligibility: Bachelor’s + basic math. (Collaborates with IBM/Germany STEM, job guarantee program.) 

14. UNEXT (formerly Jigsaw) – Trinity Circle area, Bengaluru 560008 (Old Madras Rd).

-Executive PG Program in Data Science (MIT-IBM CoE): 11 months;
-Fees: ₹1.5 L +GST ;
-Eligibility: Graduate. (Part time classes, UNext Credential.)

15. DVS Tech (DV Analytics) – Koramangala/HSR, Bengaluru.

-Data Visualization & Analytics Course: 2.5 •  months;
-Fees: ~₹20,000;
-Eligibility: Open to all. (Skill-focused, covers Tableau, QlikView.) 

16. Edureka – Doddanekkundi, Bengaluru 560048 (Indiqube Hub, Outer Ring Rd).

-Data Science •  Certification: 6 months online;
-Fees: ₹90,000;
-Eligibility: Graduate. (Instructor-led online classes, real time project.) 

17. DataTrained – Indiranagar, Bengaluru 560038 (10th A Main Rd, near metro).

-PG Diploma in DS & AI: 12 months;
-Fees: ₹1.6 L +GST ;
-Eligibility: Graduate with coding basics. (Includes specialized modules like Neural Networks.) 

18. Great Learning – Great Lakes – HSR Layout, Bengaluru 560102 (19th Main Rd, Plot 1501).

-PG Program in Data Science & GenAI: 5 months full-time classroom;
-Fees: ~₹3.15 L ;
-Eligibility: Bachelor’s. (Powered by Great Lakes University Chennai; full-time classes.) 

19. NIIT – Multiple centers (e.g. Koramangala, Jayanagar).

-PG Diploma in Data Science: 12 months;
-Fees: ₹90,000–2 L;
-Eligibility: Bachelor’s. (Well-known brand, class-room and online options.) 

20. DataKrew – Indiranagar, Bengaluru 560008 (HAL 2nd Stage).

-Data Science & Analytics Bootcamp: 6 •  months;
-Fees: ₹75,000;
-Eligibility: Graduates. (Offers practical DS and RPA modules; industry projects.) 

These courses vary by format (classroom vs online) and fee. It’s best to check institute sites for exact schedules and scholarships. A summary table below compares key aspects:

Industry Trends 2025: Job Demand and Salaries

The demand for data professionals is skyrocketing. Globally, data scientist jobs are projected to grow 36% by 2033. In India, AI/ML roles saw a 39% surge recently, and Bangalore alone holds a quarter of these openings. As per job portals, 10,000+ DS jobs are active in Bangalore. The talent gap is vast – NASSCOM estimates 1 million+ data roles needed in India by 2025.

Salary outlook: Data roles pay well even at entry-level. In Bangalore, Data Analysts earn roughly ₹3.5–6 LPA as freshers, rising to ₹9–14 LPA with a few years’ experience. Data Scientists/ML Engineers start around ₹6–12 LPA (freshers) and ₹15–25 LPA at mid-level, with senior/lead roles paying up to ₹30–50 LPA or more. Specialists in deep learning or AI can command ₹50–70 LPA. These figures align with industry surveys and hiring reports, making Bangalore highly lucrative for qualified data professionals.

Data Science Job Roles in Demand in Bangalore

Bangalore’s booming tech industry drives demand for many data-related roles. Nationally, AI/ML and analytics positions are the top tech jobs, according to NASSCOM and Indeed, and Bangalore hosts a large share of them. Key in-demand roles in Bangalore include:

• Data Scientist: Professionals who analyze large datasets to extract insights and build predictive models. They work on end-to-end projects – from cleaning data to deploying models. Despite an overall cooling in some data roles in 2023, Data Scientist positions in India remain robust. In Bangalore, companies continue hiring data scientists for domains like finance, e-commerce, healthcare and retail analytics.
  

• Machine Learning Engineer: Engineers who take data science models and put them into production. They optimize algorithms for scalability and performance, and often write production-ready code. Bangalore firms have dramatically increased hiring for ML Engineers – Naukri’s report notes a 46% YoY jump in ML Engineer openings in early 2024 – reflecting investments in AI products.
  

• Data Engineer: Specialists who build and maintain data pipelines and architectures. They ensure raw data is collected, stored, and made available for analysis. In Bangalore’s big companies, data engineers are crucial for handling the vast data volumes (often using tools like Hadoop, Spark, or cloud data warehouses). Demand for data engineering skills remains high as more organizations adopt data-driven processes.
  

• Data Analyst/Business Analyst: Analysts who focus on querying data, generating reports and dashboards, and applying basic modeling. They may not always build complex ML models, but they turn data into actionable business insights. Many Bangalore companies (from startups to MNCs) hire analysts for roles in business intelligence, marketing analytics, and financial analytics. Analysts often use SQL, Excel, and visualization tools.
  

• MLOps Engineer: An emerging role blending ML and DevOps. MLOps engineers automate the deployment, monitoring, and scaling of machine learning models. As Bangalore companies move more AI projects into production, MLOps skills (containerization, CI/CD for models, model monitoring) are increasingly valued. This role ensures models continue to perform well in real-world settings.
  

In summary, for a Data scientist in Bangalore, and related roles, the career outlook remains strong. Bangalore hosts tech companies from Amazon and Google to Flipkart and Swiggy, all of which hire for these roles. As AI adoption grows, job seekers with data science, machine learning, or engineering skills will find ample opportunities – especially given that Bangalore alone represented about 29% of the nation’s AI roles. Graduates of data science courses in Bangalore can thus target positions across industries such as IT services, finance, retail, healthcare and more.

Core Data Science Tools and Technologies 

Successful data science courses cover popular languages, libraries and BI tools. Below are the core tools to master: 

  Python: The most widely-used programming language in data     science. Its simple syntax and rich ecosystem (NumPy, pandas, scikit-     learn,   TensorFlow, PyTorch, etc.) make it ideal for data preprocessing, analysis and ML . Python supports multiple paradigms and has vast    community support. It’s the de facto first choice for analysts and machine learning engineers.

R: A statistical computing language popular in analytics and research. R shines in data visualization and statistical modeling (with packages like ggplot2 , caret , tidyverse ). It’s especially strong in bioinformatics, academia and any application needing advanced statistics. Learning R alongside Python provides a complementary skill set (many data scientists learn both). 

SQL: The standard language for querying relational databases. Nearly all data science roles require SQL skills for data extraction and manipulation. SQL’s simple declarative syntax makes it easy to retrieve and aggregate large datasets. Mastery of SQL (and variants like MySQL, PostgreSQL, or Microsoft SQL Server) is essential for cleaning data and feeding it into analytical workflow.

Power BI: A Microsoft business intelligence tool for data visualization and reporting. Power BI allows building interactive dashboards with drag-and-drop simplicity. It connects to various data sources (databases, Excel, cloud services) and uses DAX formulas for custom analytics. As many companies use Microsoft stack, Power BI skills are in high demand for dashboarding and decision support. 

Tableau: A leading data visualization platform. Tableau excels at turning complex data into interactive charts and dashboards with little coding. It’s popular for business analytics, enabling rapid insights and storytelling. Many DS courses teach Tableau to prepare students for industry projects (and it pairs well with SQL/Python for end-to-end data pipelines). 

Other tools: Data Science courses may also introduce TensorFlow/PyTorch (for deep learning), Hadoop/ Spark (big data frameworks), Excel/Sheets (for basic analysis), and ML libraries (scikit-learn). Knowledge of cloud platforms (AWS, Azure, GCP) is a bonus, as is familiarity with version control (Git). The combination of these tools depends on the course curriculum and industry focus. 

Overview of Syllabus and Skills Covered

Top programs typically cover:

• Mathematics & Statistics: Probability, linear algebra, statistics, which are foundational for algorithms.
  

• Programming: Python and/or R programming from basics to advanced data structures.
  

• Data Manipulation: Pandas (Python) or dplyr (R) for cleaning, transforming and wrangling data.
  

• Machine Learning: Core ML algorithms (regression, classification, clustering) with libraries (scikit-learn, R caret). Advanced topics like Deep Learning, NLP or Time Series may be optional.
  

• Big Data Tools: Many courses introduce Hadoop/Spark/PySpark for handling large-scale data.
  

• Databases & SQL: Structured query language, database design basics (MySQL, PostgreSQL).
  

• Data Visualization: Using libraries (Matplotlib, Seaborn in Python; ggplot2 in R) and BI tools (Power BI, Tableau) to communicate insights.
  

• Projects & Case Studies: Real-world capstone projects (finance analytics, healthcare data, e-commerce recommendation engines, etc.) help apply theory to practice.
  

• Soft Skills: Communication, storytelling, domain knowledge (finance, marketing, etc.) and interview preparation may also be included.
  

A sample course might progress: Python/R fundamentals → Data Manipulation → Statistics/ML Algorithms → Project Work. Certificates or university credits often follow completion. Many institutes invite industry experts for guest lectures.

Industry Mentors and Expert Guidance

Leading data science programs often feature guidance from industry mentors and experts. For example, Bangalore courses may involve talks or mentorship by figures like Amit Agarwal (NVIDIA’s India & Asia-Pacific BI Head), Anish Agarwal (RBC Data & Analytics Director) and Ashish Thusoo (co-founder of Qubole, ex-Facebook). These mentors provide insights on current trends (e.g. AI/MLOps) and help tailor project work to real business problems. IIT/IIM alumni and experienced data scientists from local companies (Flipkart, Google India, etc.) often engage as faculty or advisors, ensuring the syllabus stays aligned with industry needs.

Course Formats, Eligibility & Fees

Most data science programs in Bangalore require:

• Eligibility: At least a bachelor’s degree (B.Tech/B.E./B.Sc/B.Com, etc.). Strong math/statistics background is preferred. Some advanced programs (e.g. Scaler) may expect engineering graduates or work experience.
  

• Duration: Ranges from short bootcamps (3–6 months) to full PG courses (6–12+ months). Many institutes offer part-time (weekends/evenings) and self-paced online batches to accommodate working professionals.
  

• Mode: Hybrid or fully online learning is common post-pandemic. However, classroom (in-person) programs are available at facilities in HSR Layout, Koramangala, Indiranagar, etc.
  

• Fees: Highly variable. Short-term crash courses can be under ₹50k; comprehensive PG programs range from ₹1–3.5 L. Some institutes offer EMI or scholarships for meritorious students.
  

• Placement Assistance: Most top courses provide placement support (resume review, interview prep, internships). Companies hiring data talent in Bangalore include Accenture, Dell, IBM, Google, Amazon, Infosys, and many startups.

Quick Comparison Table

FAQs: Data Science Careers and Learning

Q: Which qualification is best for Data Science – certification or degree?
A: Both have value. Full-time degrees (e.g. M.Tech, M.Sc) provide rigorous foundations but take longer. Industry certificates or PG programs (like the above) are job-focused and faster. Assess your time, budget, and career goals. Many professionals combine a bachelor’s degree with a specialized DS certification to enter the field quickly.

Q: What background is required to join these courses?
A: Typically a bachelor’s degree in any field is enough. A strong foundation in math/statistics is helpful. Some courses expect basic programming knowledge; others offer refresher modules. Overall, enthusiasm for analytics and a willingness to learn coding/statistics are key – most programs cover essential skills from scratch.

Q: Can I transition to data science from a non-technical field?
A: Yes. Many programs cater to fresh graduates and career-changers. You may need to spend extra effort on fundamental programming (often taught early in courses). Highlight any analytical or quantitative skills from your background. Supplement learning with online Python/SQL tutorials before or during your course.

Q: What programming languages should I focus on?
A: Start with Python, as it’s the most popular DS language. Also learn SQL for databases. If possible, pick up R (for statistics) and at least one data visualization tool (Tableau or Power BI). Most courses teach these in their curriculum. The key is hands-on practice (projects, Kaggle, etc.).

Q: How can I maximize my placement chances?
A: Build a strong portfolio by working on real or simulated datasets (finance, healthcare, e-commerce, etc.). Complete the capstone projects seriously. Utilize institute placement support (mock interviews, CV reviews). Networking in meetups and LinkedIn also helps. Bangalore’s DS job market is competitive, so strive for internships or GitHub projects to stand out.

Q: Where can I find more career guidance and resources?
A: Explore our Data Science Career Guide for paths, interview tips, and more. Industry reports (e.g. McKinsey on analytics trends) and news portals (e.g. Analytics India Magazine) offer insights. Authoritative sources like Wikipedia or McKinsey’s State of AI survey provide macro trends. (Key reads: Data Science – Wikipedia, McKinsey AI Survey.)

Our blog combines expert-reviewed insights with latest data to help you choose and compare Bangalore’s data science courses. Each program above has been vetted for curriculum and outcomes. We’ve cited industry data and authoritative sources to ensure E-E-A-T (Expertise, Experience, Authority, Trust). If you’re aiming for a data science career in 2025, Bangalore’s offerings and job market make it a top choice. Good luck on your learning journey!

In 2025, data science continues to be one of the most sought-after careers in India, driven by the rapid growth in data generation, AI adoption, and digital transformation across industries. According to the Analytics India Magazine Jobs Report 2025, India has over 220,000 open roles in data science and analytics, with Bangalore leading as the top hiring city, followed by Hyderabad and Pune. Globally, the World Economic Forum's Future of Jobs Report 2023 highlights Data Scientists and Analysts as one of the top five growing professions, largely due to the demand for data-driven decision-making. Entry-level roles in India now offer ₹6–10 LPA, as per Glassdoor India, and career growth is strong, especially for those with hands-on experience and practical project portfolios. Students who combine technical skills (like Python, SQL, and Machine Learning) with business understanding are better positioned to stand out in interviews. Recruiters are increasingly focusing on real-world problem-solving ability, GitHub projects, Kaggle rankings, and applied knowledge over just formal degrees.

To prepare, students should adopt a structured approach: start with foundational statistics and programming, progress through tools like Pandas, Scikit-learn, Tableau, and SQL, and then move on to machine learning, deployment (using tools like Flask or Streamlit), and eventually specialize in areas like NLP, computer vision, or MLOps. Platforms like Kaggle, GitHub, and DataTalks.Club are great for learning by doing and getting community feedback. Staying updated with current trends—such as Generative AI, LLMs, and AutoML—is crucial, as they are reshaping data workflows in 2025. Free or affordable MOOCs from Coursera, edX, and Google's Data Analytics Certificate offer structured, beginner-friendly paths. Ultimately, building and showcasing projects is more important than accumulating certificates. Whether you're from a coding background or not, the key is consistency, curiosity, and a portfolio that proves what you can do—not just what you’ve learned.

References

1. https://analyticsindiamag.com/ai-trends/top-5-data-science-mentors-in-india/

2. https://www.scribd.com/document/816979179/AI-Job-Market-in-India-2024

3. https://economictimes.indiatimes.com/jobs/hr-policies-trends/indian-it-hiring-2025-promises-rebound-ai/data-science-roles-to-dominate-job-market/articleshow/116619527.cms

4. https://www.linkedin.com/pulse/data-science-2025-skills-tools-job-market-trends-analytics-zwixc/

5. https://www.infoedge.in/pdfs/News_Events_pdfs/Naukri-Jobspeak-Jan-2024.pdf

6. https://analyticsindiamag.com/ai-news-updates/indias-tech-jobs-see-20-growth-in-2025-ai-roles-surge-75/