Jump Into Data Science in Python

4.7

(5 ratings)

·

3 Weeks

·

Cohort-based Course

Stop clicking through Excel and start comfortably coding in Python with this live cohort-based course brought to you by Yale Faculty.

Course overview

Real World Data Science in 3 Weeks

Develop the most useful day-to-day data science skills by working closely with the instructors during this intensive 3-week course. Have fun alongside a group of curious students (welcoming to women and non-binary students!). This course will change your mind about coding being boring or too hard.


The class is a "flipped class", meaning you'll watch tailor-made videos at your own pace, and we'll convene 2 times a week (from 6:00-7:30pm EST) for hands-on practice. Throughout, we'll be here to answer questions and give you personal feedback. We are here for you.


This class is best for students with familiarity with datasets (eg. Excel tables), and a solid understanding of high school math, but we don't expect any coding experience.


The class is based on the top-rated class Dr. Grewal and McGowan teach at the Yale School of Environment.

Who is this course for?

01

New Data Scientists


You want to transition your career to data science, but don't know where to start

02

Curious about Coding


You've thought about learning to code, but the classes didn't seem appealing

03

Analysts / Researchers


You use Excel and know there is something more powerful out there

What will you do?

Learn Python Basics

Get started in Python using the data scientists tool of choice - notebooks - and learn how to write your code like a professional data scientist.

Load and Clean Data

The best data scientists know that understanding where your data comes from and finding all the "dirty secrets" of the data can make or break your analysis. You will learn key tools to do this.

Visualize Data

There is nothing more powerful than a chart that tells you exactly what you need to know. We cover different types of data visualizations, including maps.

Use Statistics

Start to separate the signal from the noise and reveal what your data is telling you. While we won't teach much statistics, we'll get you started.

Take the Next Step

Finally, we review how to solve your own problems when you hit roadblocks and what topics you can learn next. Data scientists are constantly learning, so this last part is important!

This course includes

Interactive live sessions

Lifetime access to course materials

44 in-depth lessons

Direct access to instructor

9 projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Expand all modules
  • Week 1

    Mar 13—Mar 17

    Week dates are set to instructor's time zone

    Modules

    • Intro

  • Week 2

    Mar 18—Mar 24

    Week dates are set to instructor's time zone

    Modules

    • Module 1: Establish Foundations

    • Module 2: Tidy-up Your Data

  • Week 3

    Mar 25—Mar 31

    Week dates are set to instructor's time zone

    Modules

    • Module 3: Check Your Data

    • Module 4: Understand Your Data

  • Week 4

    Apr 1

    Week dates are set to instructor's time zone

    Modules

    • Take the Next Step!

4.7

(5 ratings)

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Meet your instructor

Dr. Elena Grewal

Dr. Elena Grewal

Dr. Grewal was the Head of Data Science at Airbnb. At Airbnb, she spearheaded Data University which trained hundreds of non-technical people in data skills. After seven years on the rocketship, she left Airbnb and started a data science consultancy with Sarah called Data 2 the People where they do data science work for values-aligned projects in politics, criminal justice, education, and climate change. She has a Ph.D. from Stanford University and a B.A. from Yale University.

Sarah McGowan

Sarah McGowan

Today, in her work with Elena at Data 2 the People, Sarah uses Python to help clients optimize processes, scenario-plan, measure progress, and answer pressing organizational questions. Prior to co-founding Data 2 the People, Sarah was a Consultant at Bain & Co. Sarah is passionate about sharing data science skills with others and created and teaches a top-rated course at the Yale School of the Environment with Elena. Sarah has a B.E. and B.A. from Dartmouth College.

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Course Work

3 weeks, 15 hours per week
  • At-home Tutorials (Tuesdays, Wednesdays, Fridays)

    2-3 hrs per module

    Kick off new topics at your own pace with tailor-made videos and quick practice exercises. Ask instructors questions as they come up.

  • Live Workshops (Mondays and Thursdays)

    6:00PM - 7:30PM ET

    Reinforce your learning with guided problem sets that build on everything you've learned. We'll work in small group with a lot of instructor attention. When you're done, you'll get detailed, personal feedback from us on the final work you submit - we won't call it grading 😊

Course Schedule

Course Schedule
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Learning is better with cohorts

Learning is better with cohorts

Active learning, not passive watching

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Get reimbursed by your employer

Get reimbursed by your employer

Take advantage of education funds

Many employers have education budgets set aside for employees to attend courses, seminars, or conferences.

Even companies without explicit education benefits may still subsidize learning

Most managers will find ways to keep their teams growing and developing and can approve one-off expenses, even if they don't have dedicated education funds

Email Template:

Click here for an email template to ask your manager for reimbursement

Frequently Asked Questions

What happens if I can’t make a live session?
How much can I really learn in 3 weeks?
I work full-time, what is the expected time commitment?
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What if I still have questions?
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