Meet the INSAID Product Team!

Have you wondered who works the curtains behind your seamless INSAID classes? Or who ensures that any query posted by an INSAID student is given the best and fastest resolution?

It’s time you meet the dedicated Teaching Assistants at INSAID who have played a pivotal part in your journey at INSAID. We sat down with the Product Team and asked them how students interact and engage with course material, classes and faculty.

Read the interview to explore how you can structure your Data Science journey through INSAID and become a world-class Data Leader! 

Malvika: Can you tell me what the INSAID Product team does?

Mohit: The Product Team at INSAID is responsible for creating, maintaining, updating, and distributing everything the students consume. We also provide student support by solving their queries, giving suggestions, making changes based on their feedback.

The Product team also moderates and conducts the various classroom sessions as Teaching Assistants. We resolve queries posted by students during and beyond the classroom as well.  

Malvika: As part of the INSAID product team, how do you ensure relevance across course content?

Mukesh: The product team at INSAID has a number of opportunities to keep the course content at a world-class level. We work on including the latest discoveries in the Data Science and AI space in our current curriculum.

One of the ways we get a hold on people’s thought process is by responding to customer queries on several aspects related to Data Science and Python.

Also, we constantly research new products and projects along with working directly with management and users to gather and understand requirements.

We perform cross evaluation after each product is built. We make sure that the product is upto the level of pre-defined standards. These standards are defined with utmost precision and with much specificity to the objectives.

When it comes to designing course content, we keep a person from a non-coding background or someone who never heard anything about Data Science in mind. We design the course such that they could actually read and understand it on their own.

We target four techniques in specific. We work on making the course interactive, cover every topic in-depth, maintain a seamless flow throughout the length of the topic and ensure clarity for all our students.

Malvika: What are the best features of our GCD program based on student experiences?

Product Team: The GCD program is a complete journey and we try our best to make it lively throughout.

We provide constant help even if it’s the smallest of queries. The INSAID team is working towards extending 24×7 support to all its students so that the learning experience is seamless.

We also provide robust study materials under the GCD program. The next most important thing is timely assessments like quizzes, assignments and projects to let students check themselves from time-to-time.

We also support our students by clearing all queries and apprehensions on one-on-one calls.

Malvika: What are some common parameters on which you decide the kind of projects that should be a part of the curriculum?

Venkatesh:  We focus on keeping all projects strictly domain-specific.

Since our students are from all sorts of backgrounds, we try to cover up the maximum number of domains keeping in mind the spread of the cohort.

When we brainstorm on projects that need to be a part of the curriculum, we ensure they’re positively correlated to real and day-to-day complex problems in life.

It should be related to what we teach in class, but not identical in order to let students go the extra mile. If I were to elaborate, here is our approach when designing assignments & Projects:

Assignments: Questions are based on the theoretical concepts that are taught in the classes. The answers to the questions can be obtained only after executing a piece of code. This approach urges the students to think about how to solve a question practically but in a step by step process.

The questions follow a sequential order – starting from basic EDA to ML algorithm implementation and Model Evaluation. As this is the first exercise that the students will have to do after the class, the assignments will help them understand the direction that the students should travel in to reach the ultimate goal i.e; have both theoretical and practical knowledge of the concept.

Projects: Once the students complete the assignments, they will be in a position to tackle real-world problems without much guidance. Projects would require students to work on a real-world data set individually.

They encourage students to think about how to solve a problem right from the scratch given only a problem statement. The end goal of the projects is to help students evaluate if they are really equipped to solve a real-world problem without much guidance.

Malvika: How different is the student experience when it comes to programmers and non-programmers?

Product Team: Obviously there is a difference between programmers and non-programmers in class, but it is limited to the starting few weeks. 

They do have very generic questions, like how to open Python, how to code, how to run and get output, accessing Jupyter etc.

Our program is structured in such a way that we consider everyone in the class to be starting from the ground level, because even though one is a programmer that doesn’t make him a Data Scientist.

It’s how it is said:

A Data Scientist is a “person who is better at statistics than any Software Engineer and better at software engineering than any Statistician

So our motto is to maintain the balance and groom the Data Leaders of tomorrow in the best possible way.

Malvika: What are some common queries that you address for students?

Product Team: We get everything from basic, fundamental queries to more nuanced, opinionated questions. 

Students usually contact us when they need to figure out how to access the ILC (INSAID Learning Centre)

Sometimes, we get questions like Where can I find the recordings, how to open Jupyter notebook file, how to resolve errors while running, what to do when unable to read data from GitHub or when Jupyter stops working?

Where can I access the quizzes? Or how can I extend project deadlines extension. Some students need help with the coding part.

We even brainstorm Production level ML ideas with INSAID students.

Malvika: Can you explain what a Teaching Assistant does and how is he/she important to the student experience?

Varun:  As students revise through the concepts, it is possible that they might not understand a particular concept thoroughly given that they are new to the field of Data Science. At the same time, students should not wait until the next class that happens on weekends to get their doubts clarified.

Otherwise, they would get stuck without further progress and a whole week gets wasted. This is where a Teaching Assistant comes into play. Here are some ways in which a TA assists both students and faculty:

  • TA assist the faculty throughout the course
  • Stay in touch with the faculty assigned to brief him about the track
  • Share the material required to deliver the track with the faculty
  • Make announcements in the class regarding quizzes, assignments, and projects
  • Answer the queries posted by students in the class
  • Give faculty feedback whenever required


Malvika: What is an out-of-the-box initiative that you are working on right now? 

Venkatesh: I am currently researching ways of improving student experience. Recently, there is an increasing trend in the number of folks choosing online learning as it enables them to learn from industry leading experts at the comfort of their home but at the same time, online learning can look a bit alien as we are not used to this kind of environment since our childhood. We are looking at ways that make online learning as seamless as possible.

Malvika: In what ways do you think the INSAID Product team goes above and beyond to ensure dedicated student assistance?

Product team: The best way to provide student assistance is to first understand where our students come from professionally. We have students from multiple domains across all sizes of companies and professional experience. This knowledge helps us come up with the best way to deliver Product team: student assistance.

We make sure that we are not merely dealing with a question and answer system but take extra care to help them thoroughly understand the concept intuitively and at the same time important theoretical concepts are not neglected.

This was our conversation with INSAID’s Product Team. If you have any questions with the student experience at INSAID, reach out to is at




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