1. Module 1: Data Science Foundations (Week 1)
- •What data science does in business and analytics work
- •Core workflow from raw data to insight
- •Role of Python in data handling and analysis
- •Understanding datasets, variables, and basic structure
6840+ Job Posting Available
-Recruiters prefer to hire Inventateq Students - Join Inventateq NowPlacements in Data Science: 1,342
Data Science Course Online with Certification
Learn data science online with a syllabus built around Python, NumPy, Pandas, Matplotlib, and the practical tools used in real analytics work. The course also covers model-building workflows, deployment concepts, and project-style learning so you can work through data from raw files to usable insights.
4.7/5 from 1,432 reviews
Live online training you can attend from anywhere
Python-first syllabus with analytics and ML foundations
Hands-on work with data preparation and model building
Project-based sessions that mirror interview tasks
Trainer support during classes, assignments, and reviews
Certification-focused training with job-oriented direction
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Placement Assistance for Data Science Course Online
Data science hiring is rarely about theory alone. Recruiters look for people who can clean data, explain results, and speak clearly about the project work they have done. Inventateq keeps the training tied to those expectations so the course does not stop at concepts.
The support starts while you are still learning. You work through assignments, build course projects, prepare a resume around the skills you actually practiced, and then move into interview practice focused on data science and analyst roles.
Our Signature Career Support:
- Resume preparation for data science, ML, and analytics roles
- Project review support so you can explain your work clearly
- Mock interview practice around Python, SQL, and data handling questions
- Guidance on fitting your profile to roles like Data Analyst and Data Scientist
- Placement support aligned to the final certification and course portfolio
Data Science Salary Insights
Data science roles in online hiring pipelines usually start in analytics or junior model work, then grow as you handle larger datasets, better feature work, and more business responsibility. In Bangalore and other major hiring hubs, pay moves with project depth, Python strength, and how well you can communicate results.
Data Science Average Salary by Experience
Data Science Salary Insights
Data science roles in online hiring pipelines usually start in analytics or junior model work, then grow as you handle larger datasets, better feature work, and more business responsibility. In Bangalore and other major hiring hubs, pay moves with project depth, Python strength, and how well you can communicate results.
Data Science Average Salary by Experience
Why Students Choose Our Online Data Science Course?
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About Inventateq
Inventateq has supported thousands of trainees through classroom and online training, and that consistency is one reason people keep coming back to the institute. The Data Science course online is taught with the same practical style, the same support structure, and the same attention to placement readiness that the institute is known for.
We stand apart through our commitment to:
- 18,409+ trainees have trained with Inventateq across programs
- 500+ batches show steady training delivery over time
- Online, classroom, and corporate formats are part of the same teaching system
- Training stays practical, with assignments and project review built into the course
- Learners get support from instructors who are used to job-oriented training
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Inventateq Online Live Classes
Attend live, instructor-led classes from anywhere with the same hands-on structure as our classroom batches. Follow along step-by-step, get real-time doubt support, and revisit recordings whenever you need to.
100% Live Instructor-Led Online Classes
Dedicated Doubt-Solving Sessions with Mentors
Study Guides, PPTs, and Exam Guidance Included
Class Recordings and Backup Sessions for Missed Classes
Flexible Weekday and Weekend Batch Timings
Career Guidance and Interview Preparation Support
Details of Inventateq Data Science Course Online
Beginners with an analytical mind
Good for learners starting from Python and data basics, because the syllabus builds up from fundamentals.
Working professionals
Useful for people moving into analytics, reporting, or junior ML work.
Graduates from any stream
Fits learners who want a job-focused data science path rather than a theory-heavy course.
Developers moving into data roles
Helps software or IT professionals add Python data skills and model-building practice.
Analysts wanting deeper skills
Works for reporting or BI profiles that need more modern data science capability.
Career switchers
Suitable for anyone targeting data-driven roles with guided training and placement support.
Quick Highlights of Inventateq Data Science Course Online
Designed for live online learning with a structured weekly pace.
Syllabus-led format: Classes follow a step-by-step path from data basics to applied model work.
Live training: You join scheduled sessions and learn with the trainer in real time.
Assignment support: Practice tasks are part of the training flow, not added at the end.
Flexible access: The online format helps working learners and students join from different locations.
Data Science Course Curriculum
W1
2. Module 2: Python for Data Work (Week 2)
- •Python syntax for analysis tasks
- •Data types, loops, conditions, and functions
- •Writing reusable code for data operations
- •Working in a notebook-style environment
3. Module 3: NumPy Essentials (Week 3)
- •Arrays and numerical computation
- •Vectorized operations for faster processing
- •Reshaping, slicing, and selecting data
- •Using NumPy for mathematical support in analysis
4. Module 4: Pandas for Data Handling (Week 4)
- •Series and DataFrame structures
- •Loading, exploring, and cleaning tabular data
- •Filtering, grouping, merging, and sorting
- •Missing values and basic preprocessing
5. Module 5: Data Visualization (Week 5)
- •Charting data clearly with Python tools
- •Choosing the right plot for the question
- •Reading patterns, outliers, and trends
- •Presenting findings in a simple visual format
6. Module 6: Statistics for Data Science (Week 6)
- •Mean, median, mode, and spread measures
- •Probability basics used in data analysis
- •Distributions and sampling ideas
- •How statistics supports model decisions
7. Module 7: SQL for Analytics (Week 7)
- •Querying data from databases
- •SELECT, filtering, grouping, and joins
- •Using SQL to support reporting and analysis
- •Combining database results with Python work
8. Module 8: Machine Learning Basics (Week 8)
- •Supervised and unsupervised learning ideas
- •Regression and classification concepts
- •Model training, testing, and evaluation
- •Understanding overfitting and generalization
9. Module 9: Feature Work and Model Improvement (Week 9)
- •Feature selection and basic engineering ideas
- •Handling categorical and numeric data
- •Improving model quality through preprocessing
- •Comparing model performance with evaluation metrics
10. Module 10: Project Work (Week 10)
- •Guided project planning from problem to outcome
- •Working through a data science case step by step
- •Interpreting results for a business context
- •Preparing your project story for interviews
11. Module 11: Resume and Interview Preparation (Week 11)
- •Shaping a data science resume around actual skills
- •Explaining projects, tools, and outcomes clearly
- •Interview practice for analyst and entry-level DS roles
- •Final review of learning before job applications
Student Reviews – Data Science
4.7 Star Rating from 1,432+ Google Reviews
Rated 4.9/5 by AI Students
Why Learn Data Science Today?
Companies use data science to make decisions faster, reduce guesswork, and build products that respond to customer behavior. The people who can clean data, analyze it, and explain what it means are still in demand across many sectors.
Why Students Trust Inventateq for Data Science Online Training
- The online format is taught with the same project-first approach used in classroom batches.
- Learners get guided practice with the tools that matter in real data work, not only theory.
- The syllabus is built to support entry into analyst and junior data science roles.
- Training stays close to current hiring expectations around Python, SQL, and project explanation.
- Inventateq structures the course so students can move from fundamentals to interview readiness without a gap.
Build Practical Data Science Skills That Employers Can See
The course is set up to help you do real work with data, not just memorize terms. By the end, you should be able to handle datasets, explain patterns, and speak about your projects with confidence.
Turn raw data into clean analysis files
You will learn how to handle missing values, structure tables, and get a dataset ready for analysis. That skill is central to most data science and analyst roles.
Write Python for real data tasks
You will be able to use Python to explore, transform, and work through data problems. The goal is to make Python feel usable in project work, not only in exercises.
Build charts that explain a story
You will know how to choose and read the right visual format for a dataset. That makes it easier to show trends and findings in interviews or reports.
Use SQL to pull the data you need
You will be able to query tables, filter records, and combine results for analysis. This is useful in nearly every job role tied to analytics.
Understand the basic model workflow
You will see how training, testing, and evaluating a model fit into a data science process. That gives you the language to discuss machine learning work properly.
Present project work in interview-ready form
You will know how to describe what you built, what tools you used, and what the result means. This matters when you are applying for entry-level data roles.
Detailed Insights :: Online Data Science Training in Inventateq
Students Most Asked Questions
Do I need programming experience before joining?
No prior coding background is required to start, though comfort with basic logic helps. The course begins with foundation topics and builds up to data handling and machine learning concepts step by step.
Will I get hands-on projects in this course?
Yes, the training is project-driven and includes assignments that connect the lessons to practical work. You will also use project discussions to prepare for interviews later.
Is placement assistance part of the course?
Placement support is included through resume help, mock interviews, and job-readiness guidance. The support is focused on data science and analytics roles, so your profile is shaped around the work you studied.
Can non-technical students join the online course?
Yes, non-technical learners can join if they are ready to spend time on practice. The syllabus starts with basics and introduces tools in a way that makes the course manageable for career switchers.
Is the online batch live or recorded?
The online training is live. You attend scheduled classes, ask questions during the session, and follow the trainer through the exercises in real time.
How long does the data science course take?
The course is structured in weekly modules, with each section covering a specific part of the data science workflow. The exact pace depends on the batch format, but the curriculum is designed to move from fundamentals to project and interview prep in a planned sequence.
Which tools should I focus on most for interviews?
Python, Pandas, NumPy, SQL, statistics, and basic machine learning concepts are the most important parts to speak about clearly. Hiring teams usually care as much about how you explain your work as the tools themselves.
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Learn moreExplore Our Training Locations
Inventateq offers classroom training across multiple locations. Explore the branch nearest to you and check available batch timings.
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