What does a Data Scientist do?

A Data Scientist is a technically skilled, result-oriented individual who is data-driven and adept at developing complex quantitative algorithms to sort and synthesize large amounts of data and drive strategy in their organization.

Is IK's Data Science Interview Course designed only for Data Scientists working in non-FAANG companies?

This course is not just for Data Scientists working in companies other than FAANG. If you have worked as an Analyst, Applied Scientist, Research Scientist, or Statistician in your previous organizations and have some exposure to Machine Learning and Statistics; then this course is for you.

Why is system design not covered in IK’s Data Science Interview Course?

Based on our research and conversations with the instructors/hiring managers at FAANG+ companies, the system design round is not part of the interview process for data science roles such as business data scientist or product data scientist. In certain roles like applied scientist and research scientist, you may be required to have an understanding of the system design. If you plan to target a role like a machine learning engineer, in that case, system design is an integral part of the interview process, and for that, you can look out for our machine learning program.

What skills are required to become a Data Scientist?

Programming in at least one language - Python, R or MATLAB Strong Statistical knowledge such as understanding of causal impact and inference, A/B testing, hypothesis testing, etc. A good understanding of machine learning algorithms Ability to collaborate with various teams on a wide variety of problems Experience of working with databases

What qualifications are required to become a Data Scientist?

To become a Data Scientist, you should have a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, or a related field. Bachelor’s degree for an entry-level position and a Master’s degree for higher-level Data Scientist positions is required.

I am working as a Business Intelligence Analyst. Can this course help me to target roles such as Data Scientist?

If you are familiar with basic statistics and have some experience working with Machine Learning models, you can take this course to prepare for positions such as Product Analyst, Data Scientist, etc.

Switchup: Transform Your Career

Join Data Science Course to land roles at Tier-1 companies.

Kickstart your data science journey with our Data Science Course, co-created by FAANG+ data & research scientists. Deep dive into Python, SQL, Machine Learning, and more in our comprehensive data science training course.

Learn more about the course & pricing

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Data Science Course details and curriculum

PART 1: Mastering Data Science

Programming with Python

Python Programming Fundamentals

Python Data Structures and Programming Constructs

User-Defined and Built-in Python Functions and Modules

Object Oriented Programming using Python

File Handling & Exception Handling

Python for DS/ML - NumPy, Pandas, Matplotlib

Databases & SQL Programming

Introduction to Databases & SQL Programming

Advanced SQL Programming & SQL Problem Solving

Database Modelling

SQL & Database Modelling Mini Project

(Floater) Prompt Engineering & LLM Pair Programming

Mathematics for DS & ML

Descriptive Statistics and Measures of Central Tendency

Essentials of Probability & Probability Distributions

Statistical Methods

Sampling & Inferential Statistics

Hypothesis Testing

Data Wrangling & Exploratory Data Analysis

Data Wrangling & Data Transformation

Data Preprocessing & Exploratory Data Analysis

Feature Engineering

Data Analysis & Visualisation

Dimensionality Reduction

EDA Mini Project

Classical Machine Learning

Regression Algorithms

Classification Algorithms

Bagging & Boosting Techniques

Model Selection & Evaluation

Regularisation & Hyperparameter Tuning

Unsupervised Machine Learning: Clustering Algorithms

Working with Time Series Data

Modelling Time Series Data

Classical Machine Learning Mini Project

(Floater) Applications of LLMs in ML Modelling

Advanced Machine Learning & Deep Learning

Introduction to Neural Networks

Neural Architectures

Image Processing & Computer Vision

Text Processing & Transformers

Big Data Analysis

HDFS & Data Warehousing

Data Processing with Apache Spark

Cloud Computing & Big Data

Data Privacy Regulations

PySpark Mini Project

Data Visualisation & Storytelling

Data Analysis & Visualisation with MS Excel

Data Processing, Visualisation & Dashboarding with PowerBI

Data Storytelling

Advanced Visualisation & Real-Time Dashboarding

Choice of 6 Capstone Projects

Product Reviews Summary

Smart Commuting Analytics

Election Campaign Analyser

Audio Classifier & Track Recommender

Website Analytics

Stock Price Analysis

PART 2: Interview Prep

Data Structures and Algorithms Interview Prep

Sorting Algorithms

Binary Search

Arrays: Prefix Sum, Sliding Windows

Linked List

Recursion & Backtracking

Stacks and Queues

Trees

Data Science Interview Prep

Linear Regression, MLE, EM and MAP

SQL Programming

Intro to Machine Learning, Supervised Learning

Supervised and Unsupervised ML

Deep Learning and Time Series Analysis

Career & Behavioral Sessions

Interview strategy and success

Behavioral interview prep

Offers and negotiation

It's Free

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Best suited for

Why choose our Data Science Course?

Program by FAANG+ ML Engineers

360° course designed and taught by FAANG+ experts to help you become an ML Engineer

Individualized teaching and 1:1 help

Technical coaching, homework assistance, solutions discussion, and individual sessions

Capstone project

Exposure to real-life machine learning projects

Interview prep modules

Dedicated interview prep classes focused on helping you get 100% interview-ready

Mock interviews with FAANG+ ML Engineers

Live interview practice in real-life simulated environments with FAANG and top-tier interviewers

Career skills development

Resume building, LinkedIn profile optimization, personal branding, and live behavioral workshops

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Meet your instructors

Tap into the extensive hiring expertise of our seasoned instructors, boasting years of experience at industry-leading tech giants.

Our Data Science course is co-created by professionals with diverse backgrounds, encompassing roles such as Data Scientists, Principal Engineers, and Research Data Scientists across top companies including Meta, Google, Spotify, Walmart, Intel, Microsoft, and more.

Andrew Treadway

Research Data Scientist

9+ years experience

Omkar Deshpande

Head of Curriculum

15+ years experience

Qiuping Xu

Principal Scientist

9+ years experience

Abdul Salama

Manager, AI Platform

12+ years experience

Bharath Srikanth

Senior Data Scientist

7+ years experience

Bhuvan Venkatesh

Data Scientist

5+ years experience

Built for working professionals

The program schedule is designed to fit into your work and life schedule, with live classes on weekends and coaching sessions in the evenings.

Sunday

4-hour Live Classes in the morning

Consists of introduction to fundamentals, interview-relevant topics and case studies

Assignment review session

Solve questions and case studies based on the assignment shared with you

Thursday

2-hour session in the evening to discuss assignments and problem solutions

Once a week

1-hour technical coaching session to discuss any additional doubts

Practice and track progress on UpLevel

UpLevel will be your all-in-one learning platform to get you FAANG-ready, with 10,000+ interview questions, timed tests, videos, mock interviews suite, and more.

Mock interviews suite

On-demand timed tests

In-browser online judge

10,000 interview questions

100,000 hours of video explanations

Class schedules & activity alerts

Real-time progress update

11 programming languages

Get upto 15 mock interviews with

hiring managers

What makes our mock Interviews the best:

Hiring managers from Tier-1 companies like Google & Apple

Interview with the best. No one will prepare you better!

Domain-specific interviews

Practice for your target domain - Data Science

Detailed personalized feedback

Identify and work on your improvement areas

Transparent, non-anonymous interviews

Get the most realistic experience possible

More about mock interviews

1. Flexible schedule

Pick timings convenient to you

4. Technical and behavioral interviews

Uplevel your technical and behavioral interview skills

2. Remote interview experience

Mirrors the current format of remote interviews

5. Level-specific interviews

Because an L4 at Google can be quite different from an E7 at Meta

3. Feedback documentation

All the feedback you’ve ever wanted, recorded and documented

6. Interviewer of your choice

Choose based on domain

Career impact

Our engineers land high-paying and rewarding offers from the biggest tech companies, including Meta, Google, Microsoft, Apple, Amazon, Tesla, and Netflix.

Akshay Lodha

Data Engineering & Analytics

Placed at:

The experience with IK was phenomenal, it was totally worth it. After so many years I was interviewing and IK helped me a lot in orienting myself and to get into the rhythm. Had a transition from Goldman Sachs to Facebook. IK mentors guided me and told me not to worry about the preparation part and to focus on upskilling myself. That really made a huge difference.

Sayan Banerjee

Data Scientist II

Placed at:

Interview Kickstart has a very nice community. Everybody is very knowledgeable. Omkar is amazing. The way that he explains things is so great that it also taught me how to explain steps in problem solving well. Interview Kickstart's way of identifying patterns in a problem is the most effective part for me. Lastly, with the community, it enabled me to have a network of people that I can see different perspectives, and approaches to reaching solutions.

Siva Karthik Gade

Software Development Engineer

Placed at:

IK offers high-quality study material, knowledgeable and patient instructors working at industry-leading companies, well-paced live classes + tests + review sessions, always available technical + career coaches, mock interview support from the best interviewers in the respective fields. IK brings together people with same the ambition (on their platform, UPLEVEL) to guide and inspire each other

Sai MarapaReddy

Software Engineer

Placed at:

I completed IK’s program and got offers from a couple of FAANG companies. Why you should take this course: It is well tested and the focus is more on the concepts/templates rather than approaching one problem at a time. You will meet peers who have similar aspirations. You can make groups and help yourselves.

Safir Merchant

Machine Learning Software Engineer

Placed at:

I liked the course that IK provided a lot. IK provided all the knowledge on a variety of topics that helped me prepare for coding interviews. The mock interviews were really great. Landing a job at my desired company has been a great pleasure.

How to enroll for the Data Science Course

Learn more about Interview Kickstart and the Data Science course by joining the free webinar hosted by Ryan Valles, co-founder of Interview Kickstart

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FAQ: Data Science Course

How do I enroll in the program?

Interview Kickstart’s Data Science course is for anyone with strong problem-solving and analytical skills. Preferably, STEM graduates with related professional experience and recent college grads can take this course. Our comprehensive Data Science course is also suited for Software Engineers who want to transition to Data Science roles or want to take up Data Science as a skill. Also, Data Analytics and Business Analytics who wish to grow as Data Scientists with good experience in Machine Learning. Interview Kickstart has designed this Data Science course for people aiming to get into Data Science roles at top-tier companies.

I am a Data Analyst, Is Interview Kickstart’s Data Science Course beneficial for me?

If you have significant years of experience as a Data Analyst, you can apply to Interview Kickstart’s Data Science program to improve your skills. As a data analyst, you’ve likely gained proficiency in data manipulation and basic statistical analysis. The field of Data Science requires a deeper understanding of statistical concepts, Python, and R. Machine learning is at the heart of data science. The ML and deep learning concepts taught in Interview Kickstart’s Data Science program are enough to ensure you crack the interviews at big companies.

Why should I take the Data Science course from Interview Kickstart over others?

Interview Kickstart’s Data Science course stands out due to its comprehensive and extensive curriculum. Technical Skill Development: The course ensures proficiency in Python, SQL, and advanced visualization techniques. In addition to these, individuals will gain knowledge in Extensive Classical ML with Time Series, Advanced ML/DL, and Big Data Processing with Apache Spark. SOTA concepts, such as practical generative AI, are also covered. Capstone Projects: Our course allows you to choose from a variety of comprehensive projects, each tailored to address real-world problems faced by companies across various industries. Career Support: The journey doesn’t stop at imparting essential skills; Interview Kickstart provides all-rounder career support as well, where our instructors assist in Resume and LinkedIn optimization to help you secure your desired job. Furthermore, masterclass on salary negotiation empowers tech professionals to assert their value in the job market. This ensures that individuals get fair pay for their skills, thus maximizing their earning potential. Mock Interviews: The course offers a unique advantage with 15 mock interviews conducted by FAANG hiring managers. This immersive experience prepares students for real-world job interviews. Long-term support: Individuals receive 6 months of additional support, ensuring continuous guidance and assistance even after completing the course.

Who takes Data Science Mock Interviews at InterviewKickstart?

Experienced interviewers with hiring backgrounds at FAANG+ companies conduct mock interviews at Interview Kickstart.

How Many Capstone Projects Does Interview Kickstart Offer in the Data Science course?

Capstone projects include FAANG-mentored comprehensive real projects that are given at the end of the program to implement and showcase your Data Science skills. This includes actual Data Science & ML-backed Web Services, Demo Apps, Large Scale Models for business cases to help manage the transition into a new career. One can choose from 6 different mini-projects. For instance, Playlist Pulse is a music recommendation system and the aim is to create a project using advanced ML/DL algorithms to classify music tracks by mood and genre.

What Coding and Programming Skills a Data Scientist Should Know?

The required skill set and expectations from the role include the knowledge of programming languages like Python and databases like SQL. Data Scientists learn to clean, analyze, and visualize data with Python and SQL. Interview Kickstart Data Science course is divided into two parts where the first part gives extensive training on Python, SQL, Mathematics, Classical Machine Learning, Advanced Machine Learning and Deep Learning, Big Data Analysis, Data Visualisation & Storytelling, and much more. The second part prepares you for interviews so you can land a job at your dream company.

What is the average salary of a Data Scientist in the US?

As per Glassdoor, the average annual data science engineer salary is $164,000 in the United States. There is additional pay as well, which is estimated at $33,988 per year.
‍
Below is the median annual total pay for Data Scientists in the US based on years of experience.

<1 year: $95,586
1-3 years: $110,079
3-5 years: $117,460
5-7 years: $134,161
7++ years: $157,430

What is the Difference Between a Data Analyst and a Data Scientist?

The data analyst vs data scientist debate mainly focuses on their skill sets. While a data scientist is a master of advanced machine learning models, a data analyst emphasizes on performing structured data analysis and reporting.

Who Needs a Data Scientist?

Data Scientist is the fastest-growing job in the US and domains like e-commerce, education, healthcare, finance, and retail need data scientists where the role is to leverage data to drive decision-making. Data Scientists help in building personalized experiences in different industries. According to Glassdoor, the top 5 paying industries for a Data Scientist in the US are Arts, Entertainment & Recreation, Information Technology, Retail & Wholesale, Human Resources & Staffing, and Agriculture.

What’s the job of a Data Scientist?

A data scientist is responsible for analyzing complex data sets, developing predictive models, and generating actionable insights that drive business decisions and lead to success. They use statistical techniques and machine learning algorithms to solve different complex problems and contribute to enhancing organizational performance.

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Join Data Science Course to land roles at Tier-1 companies.

Next webinar starts in

Data Science Course details and curriculum

PART 1: Mastering Data Science

Python Programming Fundamentals

Python Data Structures and Programming Constructs

User-Defined and Built-in Python Functions and Modules

Object Oriented Programming using Python

File Handling & Exception Handling

Python for DS/ML - NumPy, Pandas, Matplotlib

Introduction to Databases & SQL Programming

Advanced SQL Programming & SQL Problem Solving

Database Modelling

SQL & Database Modelling Mini Project

(Floater) Prompt Engineering & LLM Pair Programming

Descriptive Statistics and Measures of Central Tendency

Essentials of Probability & Probability Distributions

Statistical Methods

Sampling & Inferential Statistics

Hypothesis Testing

Data Wrangling & Data Transformation

Data Preprocessing & Exploratory Data Analysis

Feature Engineering

Data Analysis & Visualisation

Dimensionality Reduction

EDA Mini Project

Regression Algorithms

Classification Algorithms

Bagging & Boosting Techniques

Model Selection & Evaluation

Regularisation & Hyperparameter Tuning

Unsupervised Machine Learning: Clustering Algorithms

Working with Time Series Data

Modelling Time Series Data

Classical Machine Learning Mini Project

(Floater) Applications of LLMs in ML Modelling

Introduction to Neural Networks

Neural Architectures

Image Processing & Computer Vision

Text Processing & Transformers

HDFS & Data Warehousing

Data Processing with Apache Spark

Cloud Computing & Big Data

Data Privacy Regulations

PySpark Mini Project

Data Analysis & Visualisation with MS Excel

Data Processing, Visualisation & Dashboarding with PowerBI

Data Storytelling

Advanced Visualisation & Real-Time Dashboarding

Product Reviews Summary

Smart Commuting Analytics

Election Campaign Analyser

Audio Classifier & Track Recommender

Website Analytics

Stock Price Analysis

PART 2: Interview Prep

Sorting Algorithms

Binary Search

Arrays: Prefix Sum, Sliding Windows

Linked List

Recursion & Backtracking

Stacks and Queues

Trees

Linear Regression, MLE, EM and MAP

SQL Programming

Intro to Machine Learning, Supervised Learning

Supervised and Unsupervised ML

Deep Learning and Time Series Analysis

Interview strategy and success

Behavioral interview prep

Offers and negotiation

Next webinar starts in

Why choose our Data Science Course?

Program by FAANG+ ML Engineers

Individualized teaching and 1:1 help

Capstone project

Interview prep modules

Mock interviews with FAANG+ ML Engineers

Career skills development