Becoming a Data Scientist is not easy. It takes more than just mastering skills like statistics, data wrangling, and visualization. You need to learn how to ask the right questions and weave a story around your findings.

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In this self-paced online course, you'll:

  • Build a solid foundation in Data Science
    and cover a breadth of topics including R, statistics, data wrangling and visualization.
  • Work on real-world problems
    and build a portfolio of data-projects that you can showcase to employers.
  • Work 1-on-1 with an expert mentor
    to get feedback on your projects and seek career advice.

By the end of this course, you'll be able to:

  • Analyze large datasets and make data-driven decisions.
  • Tell a story with data, and communicate effectively with all stakeholders.
  • Apply for data analytics and junior data scientist roles; take on freelance data projects.

By the end of this course, you'll be able to:

  • Analyze large datasets and make data-driven decisions.
  • Tell a story with data, and communicate effectively with all stakeholders.
  • Apply for data analytics and junior data scientist roles; take on freelance data projects.

This course is made for you.

Whether you are looking to launch a new career in Data Science, or just looking to use data to derive business insights in your current role, this course is right for you. Past students who have taken this course include:

Fully Online, But With The Human Support You Need to Succeed

  • Learn online, from anywhere

    • All you need is a laptop and an internet connection. You can be in any country or time zone. We've taught students from 6 continents!
  • Build real projects, earn a certificate

    • We believe you learn best by doing. Our 100+ hour curriculum is designed around 7 real-life projects. Graduate with a portfolio that you can show to employers. Earn a certificate of completion, signed by your mentor.
  • The best curriculum on the web

    • We collaborated with data science experts who have worked at companies like IBM, Dell, and Cisco to build a curriculum that combines the best resources on the web. Experts keep the curriculum updated, to ensure you're learning what's most relevant to employers.
  • The (career) support you need

    • We're here to help you succeed. You'll get 1:1 feedback and career guidance from your expert mentor. When you have questions, you'll get near-real-time answers in our Community.
  • Set your own pace

    • You can go as fast as you like. We know you probably have a full-time job, and we designed the program to fit your schedule.

Jumpstart your career in Data Science!

Our 130-hour extensive, tailored curriculum includes 40+ hours of project work.

Learn how to run statistical analyses in R - a programming language which is popular in both academia and industry


R, a programming language designed for statistical analysis, is one of the most prominent languages in the data science world (the other being Python). Its many libraries & packages and its plotting capabilities, make it a great tool for beginners. In this module, you’ll learn to program in R from scratch. In addition to the language itself, you'll become proficient at several R-based tools which data scientists in industry use in their day-to-day work.

Topics Covered

  • R syntax
  • Install R and RStudio (a programming environment for R)
  • Use R Markdown to create beautiful reports in R
  • Version control with Github and Rstudio to maintain and share your project portfolio

Estimated Time: 15+ Hours

Learn how to clean your data, so that you can start analyzing it sooner


Before you run any cool algorithms to get insights from data, you need to clean and transform it in a form that you can actually work with. This process is called data wrangling. It is estimated that data scientists in industry spend the most time on data wrangling, usually with the help of semi-automated tools. In this module, you'll learn the most common tools and workflows in R that make this normally onerous task a snap.

Topics Covered

  • R packages for data wrangling - dplyr and tidyR
  • The split-apply-combine paradigm - a general technique to structure complex data transformations
  • An elective on regular expressions, which lets you find simple patterns in text

Projects

  1. Submit your proposal for the Capstone Project
  2. Work on some (relatively) simple data wrangling exercises to get your feet wet
  3. For those who really want to master data wrangling, clean up a dataset collected by fitness apps from smartphone accelerometers

Estimated Time: 12+ Hours

Understand the mathematics behind your analysis


At this stage, you know how to collect and clean data, and you are ready to dive into actual analysis. However, analyzing data is not just about applying a bunch of algorithms blindly; it's crucial to understand how they work, when to use them and the assumptions they make. We start with a gentle but thorough introduction to the field of statistics, which forms the mathematical foundation of data science.

Topics Covered

  • Random variables & distributions
  • Descriptive statistics (averages and spreads)
  • Regression to identify correlations between different quantities
  • Hypothesis testing and inferential statistics to draw inferences about your data from smaller samples

Estimated Time: 22+ Hours

Find trends and summarize your data to sharpen your hypothesis


Once a data set is clean and ready to analyze, Exploratory Data Analysis (EDA) is a set of techniques that helps a data scientist identify the most important trends and characteristics of the data.

Topics Covered

  • EDA vs classical & Bayesian approaches
  • Exploring data through plots: histograms, frequency polygons, box-plots, quartiles, scatter plots, heat maps 

Projects

Using a data set on diamond prices, try out various exploratory data analysis techniques.

Estimated Time: 11+ Hours

Learn how to tell a story with data - and communicate your findings better


If there's one thing that most data scientists would have loved to know before they entered the field, it's that data science is not just about the math, the algorithms and the analysis, it's also about telling a good story. In real life, data scientists don't work in a vacuum - there's always a client, internal or external, waiting on the results of their work. As a result, storytelling is a critical skill for data scientists. In this module, you'll learn how to tell a great data story by watching several masters of the art at work.

Topics Covered

  • A talk on the importance of storytelling by DJ Patil
  • A world-famous TED talk by Hans Rosling, showing the power of storytelling combined with statistics

Projects

This is about the time you'll be expected to turn in your Capstone Project Milestone. Your milestone is a data story based on your initial exploration of your data.

Estimated Time: 4+ Hours

Apply Machine Learning technique to real-world data problems


In this module, we get to Machine Learning, a set of tools and algorithms that lets us make predictions and find patterns automatically in complex data sets. Learn how to apply these techniques to real-world applications from examples including Moneyball, eHarmony, Twitter, IBMWatson, and Netflix.

Topics Covered

  • Feature Engineering
  • Linear & Logistic Regression
  • Clustering, Model Evaluation
  • Cross-Validation
  • Electives on Trees and Text Analytics

Estimated Time: 29+ Hours

Learn how to convey all your insights in one beautiful frame


We’ve talked about data storytelling before, and you know how important stories are in conveying your insights to stakeholders. But how do you make stories compelling? How do you ensure that you really drive your message home? As in many other aspects of life, “a picture is worth a thousand words” here. Visual representations play a big role in how effectively information can be assimilated, so learning how to create engaging and meaningful visualizations is essential for a data scientist.

Topics Covered

  • Visual perception & graphic design
  • Advanced visualization techniques like index charts, horizon graphs, parallel co-ordinates, maps, hierarchies & networks 

Estimated Time: 6 Hours

Now put together everything that you have learnt


The Capstone Project is a key part of our curriculum that every student must complete. The project is designed to provide you with the experience of working in a realistic data science scenario. Working with your mentor, you'll pick a data set and a problem of interest. From the start to the finish, your project will be targeted to a specific client (real or imaginary). Using the data science techniques you've learned, you'll not only come up with a reasonable solution to the problem, but learn to present it to them as a compelling story.  

Estimated Time: 10+ Hours

All you need to get cracking on the job-market


Now that you have a foundation in data science, you're probably interested in what it takes to actually get a job in the field. We've collected a plethora resources for you to understand what data science jobs and interviews in the real world are like. 

Topics Covered

  • Preparing for interviews
  • Interviews with data scientists
  • Building data products
  • Design thinking for Data Scientists
  • Advice for strengthening portfolio
  • Websites and people to follow

Request a Detailed Syllabus

Get mentored, each week, by an industry expert

Once you enroll, we'll pair you with a mentor. In your weekly 1-on-1 video calls, you can ask your mentor questions, get project feedback, or seek career advice. We know that learning online is challenging. Working with a mentor keeps you accountable. and gives you a window into the world of a real data scientist. Our mentors are hand-picked for their expertise and love of teaching.

You’ll be in good company. Here are some of the fine organizations where our students came from or went to.

Learn at your own pace, just $499 / month

We estimate the total effort required of you at 100 hours. Most working professionals are able to complete in 3 months. You're welcome to choose your own pace. The more time you devote, the less the program will cost.

Here are some scenarios for how much the course might cost you.
Time Per Week 13-20 hours
It will take you 2 months
It will cost you $998
Time Per Week 9-13 hours
It will take you 3 months
It will cost you $1497
Time Per Week 7-10 hours
It will take you 4 months
It will cost you $1996

When can I start?

Our next available course starts on Oct 24th. (All start dates before that sold out in advance.)

Enrollment Closes 1-2 weeks before the course start date.
21 Days Left!

Become a Data Scientist!

The sooner you reserve your spot, the sooner we can match you with the perfect mentor.

Frequently Asked Questions

This workshop lets you learn at your own pace and pay by the month - for only as long as you want to continue. If you don't love it in the first one week, we will give you a full refund. The $499 monthly subscription covers: 1. Full curriculum of courses and materials used in the workshop.
2. Weekly 1-1 video calls with your personally matched mentor.
3. Access to an exclusive community with expert mentors and fellow participants.
4. Help on your questions & project feedback through mentor calls, community & weekly Office Hours.
5. All taxes and fees.
Learn at your own pace! The total estimated workload is 120+ hours - you can make it an intensive one-month sprint, or take longer as you please.
We work with industry experts to pick the best learning resources on Data Science and structure them into a logical curriculum. Note that the individual resources need not be authored in-house, but are curated from the best in the field. We do provide the glue that stitches everything together and fills gaps, if any. We believe this is our unique strength because we stand on the shoulders of giants, instead of being restricted to in-house content. Think of us as a college professor who creates a curriculum with the most formidable book chapters, research papers, projects instead of teaching from only her own textbook.
You’ll interact 1-on-1 with your personal mentor in weekly, 30-minute video calls. There will be weekly Office Hours hosted by two of the mentors. You will also have access to a exclusive community of mentors and fellow learners. You can ask questions and receive project feedback through the mentor calls, office hours or the community.
We will provide certificates of completion to all the participants who complete the workshop and successfully complete the final project.
The workshop will happen in a completely online, self-paced, mentor-aided format. All you need is an internet connection.
Some background in programming (basic familiarity with variables, functions, loops, etc; any language ok) is helpful. Other than that, beginners are welcome!
Absolutely! In fact, it is a great idea! In the past, our students have been sponsored by their employers, and companies are more than willing to invest in their employees' learning & development. Do check with your employer if they can support your subscription fee from the learning budget.
Unanswered question?
Get in touch!