Chandan's Journey with the IITM Pravartak Data Analytics Certification

Table of Contents

Click to view topics covered in this learner story

Starting a career in Data Analytics can be confusing when there are dozens of tools, courses and learning resources to choose from. The bigger challenge is often figuring out how these individual skills fit together and how to practise them in a structured way.

For Chandan, the goal was to build practical Data Analytics skills while following a defined learning path. He wanted to understand the tools used in analytics, work on projects and have access to people who could help when he got stuck. At the same time, earning a certification associated with an established academic institution was an important part of his decision.

After exploring his options, Chandan enrolled in the Professional Certification in Data Analytics with GenAI by IITM Pravartak - TIH.

His experience went beyond completing individual lessons. It involved understanding the program before enrolling, progressing through the curriculum, working on projects, using doubt support, interacting with mentors and experts, attending IIT faculty sessions and understanding how the certification fit into his overall learning journey.

This is Chandan's experience with the program, with a focus on what he learned, how the support system worked and what he found useful about the overall structure.

Why Chandan Started Learning Data Analytics

Before joining the program, Chandan knew that learning Data Analytics would require more than becoming familiar with individual software tools. Excel, SQL, Power BI and data analysis each involve different concepts, and he wanted to understand how they worked together as part of a larger analytics process.

He also wanted to understand the growing role of Generative AI in analytics. AI tools are increasingly becoming part of how professionals work with information, automate repetitive tasks and explore data. For Chandan, learning these capabilities alongside core analytics skills was more useful than treating them as completely separate subjects.

His main questions were practical: What should he learn first? Which tools should he prioritise? How could he practise what he learned? Who could help when he faced a difficult concept? And how could he turn his learning into projects that demonstrated his skills?

“I wanted a structured path where I could learn the fundamentals, practise them through projects and get guidance whenever I needed it.”

What Chandan Looked for Before Enrolling

Chandan did not want to choose a program based only on its name or certification. He wanted to understand what the actual learning experience would look like after joining.

The curriculum was one of the first things he looked at. He wanted the program to cover the foundational skills required in Data Analytics while also introducing newer AI-based tools and workflows.

The learning format was another consideration. Having live learning, assignments, tests, practical projects and access to support meant that he would not have to design the entire learning process himself.

The certification also mattered to him. The Professional Certification from IITM Pravartak - TIH gave the program an academic and institutional component alongside the practical learning experience.

He also wanted to know what would happen when he had doubts. The availability of Teaching Assistants, Ninja AI, a Relationship Manager and industry expert sessions made the support structure an important part of his evaluation.

His First Step Towards Joining Coding Ninjas

Before making the final decision, Chandan spoke with a Coding Ninjas academic counsellor. The conversation helped him understand the curriculum, learning format, support system and certification structure.

This stage was useful because he wanted clarity about what would happen after enrolment rather than relying only on the information available while comparing programs.

Once he had a better understanding of how the different components fit together, he decided to join the program and begin the six-month learning journey.

IITM Pravartak Data Analytics Course Overview

The Professional Certification in Data Analytics with GenAI by IITM Pravartak is structured as a six-month program combining core Data Analytics skills, Generative AI, practical projects and guided learning support.

The current curriculum begins with an introduction to Data Analytics, the Data Analysis Lifecycle and MS Excel. It then progresses into Power BI, data transformations, Power Query and data modelling, followed by SQL and database operations. The program also incorporates Generative AI tools, practical workflows and projects.

The current course information also highlights 20+ tools and technologies, 10+ projects and AI-based projects and workflows. The program provides ongoing doubt support through Teaching Assistants and Ninja AI, along with a Relationship Manager and opportunities for expert interaction.

• Program: Professional Certification in Data Analytics with GenAI by IITM Pravartak - TIH
• Duration: 6 months
• Core learning: Data Analytics, Excel, Power BI, SQL and Generative AI
• Practical learning: Projects, assignments, tests and AI-based workflows
• Support: Teaching Assistants, Ninja AI and Relationship Manager
• Expert interaction: IIT faculty guest lectures and industry expert sessions
• Certification: Professional Certificate from IITM Pravartak - TIH, along with Coding Ninjas module-wise certification

Learning Through the Structured Curriculum

One of the most important parts of Chandan's experience was having a defined sequence to follow. Instead of trying to learn Excel, Power BI, SQL and AI tools independently, the curriculum provided a progression through different stages of Data Analytics.

The initial modules introduced Data Analytics and the Data Analysis Lifecycle before moving into MS Excel. This created a foundation for understanding how data can be organised, cleaned and analysed.

The next stage moved into Power BI. Chandan worked through concepts around data transformations, Power Query and data modelling. This helped him understand that dashboard creation is not simply about creating charts. The underlying data needs to be prepared and structured before useful insights can be presented.

SQL introduced another important part of the analytics workflow. Working with databases and understanding operations on data gave him another way of approaching analytical problems.

The value of this structure was that each topic did not remain isolated. As Chandan progressed, the relationship between data preparation, analysis and visualisation became clearer.

Applying Concepts Through Projects

Projects became an important part of the learning experience because they gave Chandan an opportunity to move from understanding a concept to actually applying it.

The current program highlights AI-based projects and workflows across use cases such as US healthcare, credit risk analysis, meal plan analysis and Pro Kabaddi analysis. The course information also states that 10+ projects are reviewed by certified experts for feedback and guidance.

Working on projects required him to think beyond individual commands or features. He had to understand the data, determine what needed to be analysed and consider how the output could be communicated.

This practical component also gave context to the theoretical concepts. For example, learning about data transformations becomes more meaningful when the learner has to prepare an actual dataset before analysing it.

For Chandan, this was one of the more useful aspects of having a structured program. The projects provided a reason to revisit concepts and understand how different tools could work together.

Understanding Generative AI in Data Analytics

Another important part of the program was its AI-infused approach to Data Analytics.

Chandan was not learning traditional analytics in isolation. The program introduces Generative AI tools and workflows alongside the core analytics curriculum, helping learners understand where AI can fit into modern data-related work.

The current program information highlights 20+ tools and technologies and a range of AI-based projects and workflows.

For Chandan, this helped put AI into context. Instead of treating Generative AI as a completely separate subject, he could think about it as an additional capability that can support parts of an analytics workflow while the underlying Data Analytics concepts remain important.

Learning Support, Mentors and Teaching Assistants

Learning independently can become difficult when a concept is unclear or a project is not working as expected. Having access to support was therefore an important part of Chandan's experience.

The current program provides 24/7 doubt support through Teaching Assistants and Ninja AI. This gives learners multiple ways to seek help while working through concepts, assignments and projects.

Ninja AI can be useful for quick technical questions, while Teaching Assistants can provide human guidance when a learner needs additional explanation or context.

Chandan also had access to a dedicated Relationship Manager. This provided a non-technical point of contact throughout the learning journey and helped make the overall experience more structured.

Beyond day-to-day doubt support, the program also provides 1:1 industry expert sessions. These sessions can help learners understand their projects, professional profile and preparation for the next stage of their journey.

Learning Through IIT Faculty Guest Lectures

The opportunity to attend IIT faculty guest lectures was another part of the program that stood out to Chandan.

The current program includes a monthly guest lecture series featuring faculty from a pool of IITs. The purpose is to give learners exposure to emerging technology and industry trends beyond the regular curriculum.

These sessions added another layer to the learning experience. While the core curriculum provided the structured technical foundation, guest lectures offered an opportunity to hear different perspectives from academic experts.

For Chandan, this interaction contributed to the broader value of the program because the learning experience was not limited to recorded lessons or assignments.

Understanding the IITM Pravartak Certification

The certification was one of the factors Chandan considered while evaluating the program.

The program is offered in collaboration with IITM Pravartak - Technology Innovation Hub, and successful learners receive a Professional Certificate from IITM Pravartak - TIH. The learning journey also includes Coding Ninjas module-wise certificates.

For Chandan, the value of the certification was connected to the overall learning experience rather than being viewed in isolation. The certificate was accompanied by a structured curriculum, practical projects, expert interaction and learner support.

This distinction mattered to him. A certificate can document that a learner completed a program, but the learning experience around that certificate determines how much practical value the learner takes away from the program.

In his case, the combination of the IITM Pravartak certification, Data Analytics curriculum, project work, mentorship and expert interaction made the program feel like a complete learning journey rather than simply a certification course.

Career Preparation and Support

Although Chandan's primary focus was learning Data Analytics, he also wanted to understand how his new skills could be presented professionally.

The program's career-support ecosystem includes resume reviews, profile-building assistance, mock interviews, 1:1 industry expert sessions and access to the Coding Ninjas Job Cell.

This support was useful as Chandan began connecting his curriculum with professional expectations. His projects, technical skills and certification needed to be presented clearly when he discussed his background.

Mock interviews also provided an opportunity to practise explaining technical concepts and projects. This helped him think about not just what he had learned but how clearly he could communicate that learning.

The career-support component remained one part of the larger experience. The main foundation of the journey was still the curriculum, practical work, mentorship and support that helped him build his skills.

Eventually, Chandan secured a job offer through the career-support process. For him, this became an outcome of the broader learning and preparation journey rather than the only measure of the program.

Chandan's Overall Experience With the IITM Pravartak Program

Looking back at the experience, Chandan's journey was shaped by several components working together.

The structured curriculum gave him a defined path through Data Analytics, beginning with fundamentals and progressing through Excel, Power BI and SQL while incorporating Generative AI. The projects gave him opportunities to apply what he learned instead of limiting the experience to theoretical lessons.

The support ecosystem was another important part of the journey. Teaching Assistants and Ninja AI helped with doubts, while the Relationship Manager provided an additional point of contact. Industry expert sessions offered another layer of guidance as he started thinking about professional development.

The monthly IIT faculty guest lectures added academic and industry context to the learning experience. These sessions complemented the regular curriculum by exposing learners to perspectives beyond their individual modules.

Finally, the IITM Pravartak Professional Certificate gave the learning journey an institutional credential. For Chandan, the certificate was most meaningful when considered alongside the curriculum, projects, expert interaction and support system that came with it.

His eventual job offer was an important outcome, but his overall experience was built around learning and preparation. For learners evaluating an IITM Pravartak Data Analytics course, his journey highlights several factors worth examining beyond placement claims: how current the curriculum is, what projects are included, what kind of mentorship is available, how doubts are handled, how learners interact with experts and what certification they receive.

These elements together provide a more complete picture of what the learning experience can look like for someone considering a structured Data Analytics and GenAI program.

Frequently Asked Questions