Becoming a Senior Data Scientist is not easy. It takes more than just mastering basic skills like statistics, data wrangling, and visualization. You will need to develop one area of technical analytic expertise, while being conversant in many others.

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

  • Learn advanced data science
    topics like machine learning, inferential statistics, and data storytelling.
  • Work with a mentor on a project
    (of your choice), and build an online portfolio.
  • Get career support
    (resume review and interview prep) to get you in shape for the Data Science job market.

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

  • Build data products that integrate with production-grade software
  • Apply for most entry-level Data Scientist jobs (with a portfolio to show)
  • Participate in Kaggle competitions

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

  • Build data products that integrate with production-grade software
  • Apply for most entry-level Data Scientist jobs (with a portfolio to show)
  • Participate in Kaggle competitions

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 hired experts with experience at companies like IBM, Dell, and Cisco to build a curriculum that combines the best resources on the web. Experts review the curriculum frequently, to ensure you're learning what's most relevant in the industry.
  • 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 Slack 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 120-hour extensive, tailored curriculum includes 60+ hours of project work.

Python is one of the languages that has become the lingua franca of data science (the other being R). In this module, you'll learn to program in Python and start using an ecosystem of useful and powerful Python-based tools for doing data science and building an online portfolio.

Topics Covered

  • Python
  • iPython Notebook
  • Matplotlib
  • Pandas
  • Git and Github

Estimated Time: 5+ Hours

It is estimated that data scientists in industry spend the most time on data wrangling i.e. cleaning the raw data and getting it into a format amenable for analysis, usually with the help of semi-automated tools. In this module, you'll learn the most common tools and workflows in Python that make this normally onerous task a snap.

 

Topics Covered

  • Deep Dive into Pandas for Data Wrangling
  • Data in files: Work with a variety of sources from unstructured/semi-structured text files (.txt) to delimited/structured/nested format files like excel, csv, json, xml etc.
  • Data in Databases: Get an overview of relational and NoSQL databases and practice data manipulation with SQL.

 

Estimated Time: 17+ Hours

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. A data story is a powerful way to present insights to your clients, combining visualizations and text into a narrative. But storytelling is an art, and needs creativity. This section will try to get your creative juices flowing by suggesting some interesting questions you can ask of your dataset, and a few plotting techniques you can use to reveal insights.

 

Project

 

You’ll practice the concepts learned by creating a data story.

 

Estimated Time: 10+ Hours

Statistics is the mathematical foundation of data science. Within statistics, inferential statistics is a set of techniques that helps us identify significant trends and characteristics of a data set. Not only is it useful to explore the data and tell a good story, but also opens the way for deeper analysis and actual predictive modeling. In this module, we cover several important inferential statistics techniques in detail.

Topics Covered

  • Theory and application of inferential statistics
  • Parameter estimation
  • Hypothesis testing
  • Statistical significance
  • Correlation and regression
  • A/B Testing

Estimated Time: 13+ Hours

Machine Learning combines aspects of computer science and statistics to extract useful insights and predictions from data. Machine Learning is what lets us make useful predictions and recommendations, or automatically find groups and categories in complex data sets. In this module, we'll cover the major kinds of machine learning algorithms (supervised and unsupervised), with several techniques within each of them. You'll learn when these algorithms are useful, the assumptions they incorporate, the tradeoffs they involve and the various metrics you can use to evaluate how well your algorithm performs. 

 

Topics Covered

  • Scikit-learn
  • Supervised and unsupervised learning
  • Naive Bayes, SVM, Decision trees, Regression, clustering, recommender systems
  • Advice for applying machine learning
  • Dimensionality reduction
  • Validation and evaluation of machine learning

Estimated Time: 48+ Hours

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: 25 Hours

Topics Covered

  • Preparing for interviews
  • Interviews with data scientists
  • Building data products
  • Design Thinking for Data Scientists
  • Advice for strengthening portfolio

Request a Detailed Syllabus

Get mentored by top industry experts

You’ll have 30 minute 1:1 video calls with your mentor for feedback, answers to your questions and real-world career  advice. Our mentors are hand-picked based on their love of teaching and experience.

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 120+ 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 15-23 hours
It will take you 2 months
It will cost you $998
Time Per Week 10-15 hours
It will take you 3 months
It will cost you $1497
Time Per Week 7-11 hours
It will take you 4 months
It will cost you $1996

When can I start?

Our next available course starts on Jan 2nd. (All start dates before that sold out in advance.)

Enrollment Closes 1-2 weeks before the course start date.

Enrollment
starts soon!

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.
You should have a strong background in Probability & Statistics, and should be very comfortable programming in at least one language. If you do not meet these requirements, please check out our Foundations of Data Science workshop instead.
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!