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Bootcamp Prep Course

Beginner Python and Math for Data Science

Part-Time, Live Online Course

Considering applying to our Data Science and Analytics Bootcamps but need to build or brush up on your basic skills first? Our Beginner Python & Math for Data Science course was designed for you, the beginner looking for an introduction to the building blocks essential to developing data science skills or forging a new career in the field. This course sets you on the right track, covering everything you’ll encounter during the bootcamp application process. You’ll learn:

  • Introduction to programming in Python
  • Common Python libraries: NumPy, Pandas, Matplotlib
  • Foundations of linear algebra
  • Foundations of calculus
  • Foundations of probability
  • Foundation of statistics

Course Co-designer Roberto Reif, Senior Data Scientist, Metis and Gordon Dri, Data Scientist, Oracle
The Beginner Python and Math for Data Science course was instrumental in preparing me for the Metis Bootcamp Application. I was able to improve my Python skills and brush up on my math fundamentals, which ultimately enabled me get accepted and successfully complete the Bootcamp.
Carolina Gonzalez,
Business Intelligence Analyst, Outreach

Who the course is designed for:

Those interested in applying to our Data Science and Analytics Bootcamps but who have little to no prior experience or need a refresher with fundamental Python programming and/or math concepts necessary to succeed at the next level. The only prerequisite is to have Python installed.

Outcomes

  • The ability to tackle courses in data science, particularly our Introduction to Data Science part-time course and full-time immersive Data Science and Analytics Bootcamps.
  • An understanding of the fundamentals of mathematical concepts in linear algebra, calculus, probability, and statistics.
  • The ability to write Python code to solve mathematical problems using linear algebra, calculus, probability, and statistics.
Have questions? Get answers to frequently asked questions. FAQs

What you'll receive upon completion:

  • Certificate of completion

Dates & Instructors

Live Online
Discounted Tuition $499 $750

Beginner Python and Math for Data Science

August 23 to October 4

Mondays and Thursdays

6:30 - 9:30PM PST

33% savings on tuition through rest of 2021. There will be no class on Sept. 6th.

Adam Wearne
Instructor

With a background in physics and quantitative finance, Adam has applied data science and machine learning solutions in a wide variety of research settings ranging from recognizing and clustering behavioral patterns to applying natural language processing techniques to help build superior equity portfolios. Previously a Senior Data Scientist at Metis, he is now a Senior Artificial Intelligence Engineer at Bond Financial Technologies, Inc. Adam is passionate about teaching and is excited to share his industry experiences with students.

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Live Online
Discounted Tuition $499 $750

Beginner Python and Math for Data Science

September 27 to November 4

Mondays and Thursdays

6:30 - 9:30PM EST

33% savings on tuition through rest of 2021.

Heather Hardway
Instructor

Heather is a Data Scientist at iHeartMedia. Heather started her career studying mathematics, specializing in modeling applications to biological systems. After receiving a PhD and leaving academia, she transitioned to data science, working in a variety of industries, including finance, consulting, retail, and government. Getting back to her roots, she enjoys combining her love teaching mathematics with her experience of applying data science to real-world problems.

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Live Online
Discounted Tuition $499 $750

Beginner Python and Math for Data Science

October 25 to December 6

Mondays and Thursdays

6:30 - 9:30PM EST

33% savings on tuition through rest of 2021. There will be no class on Nov. 25th.

Anastassia Kornilova
Instructor

Anastassia is a Research Scientist at FiscalNote, where she uses Machine Learning and Natural Language Processing to create insights from legislative and regulatory data. Over her four and a half year tenure, Anastassia has run a number of projects ranging from forecasting if legislation will pass to identifying key words and topics in text. In addition to building platform features, Anastassia has authored several papers for top-tier Natural Language Processing. Previously, she received a bachelors degree in Computer Science from Carnegie Mellon University. She loves to spend her free time outside, hiking, climbing and skiing.

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Prerequisites

  • There are no prerequisites for this course - if you’re an absolute beginner or just interested in data science, this course is for you! Students must have a Github account to get access to the content. Sign-up for an account on their site is free, fast and easy.
  • Students only need to be able to install and verify the installation of Anaconda (for Python 3) by running a "Hello World" sample code.
Considering our immersive data science bootcamp?

Part-time course alumni can apply the amount of tuition paid for one part-time course towards enrollment in an upcoming bootcamp upon admittance.

Course Structure & Syllabus

Week 1
Python Basics

Get an introduction to programming in Python. Learn how Jupyter Notebooks work, and cover the basics of programming including data structures, data operations, if else statements, for and while loops, and logical operations.

Week 2
Python Advanced

Learn advanced functionality in Python, including functions, debugging, error handling, string manipulations, and writing efficient code.

Week 3
Python Mathematical Libraries

Learn about using libraries that are useful for data manipulation and visualization. Specifically, we will be using NumPy, Pandas, and Matplotlib. These libraries will allow us to load and save data, manipulate data such as aggregating, filtering, detecting outliers, and visualizing.

Week 4
Linear Algebra

Learn the fundamentals of linear algebra, including vectors, and vector manipulations, matrices and matrix manipulations, linear equations and solutions, eigenvalues and eigenvectors.

Week 5
Calculus and Probability

Learn the fundamentals of calculus and gain an intuition for derivatives, integrals, determining local maximum and minimum, and limits. Similarly, we will cover an introduction to probability and learn about random variables, mean, variance, probability mass and density functions, and cumulative distribution functions.

Week 6
Statistics

Learn the basics of statistics and its applications. Some topics include ANOVA, hypothesis testing and p-value, and confidence intervals.

Live Online Interactive Learning

Learn from world-class data science practitioners.

Our Live Online instructors bring deep industry experience from a broad range of industries and companies including Viacom, Spotify, and Capital One Labs. You’ll have an Instructor and Assistant Instructor to support you throughout your learning process.

Interact with instructors and classmates in real-time.

This course is truly live, which means you can interact with the instructors and your fellow students in real-time. Stay engaged by asking questions and participating in polls and conversations, and join your course Slack channel for additional support, communication, and collaboration.

Learn online without sacrificing the value of live instruction.

The world is your classroom. Log in from wherever you are and gain access to live, interactive data science instruction that will push your career further in the right direction. In case you have to miss a class, you can access all recordings 24/7 to stay caught up and refer back.

Register for an on-demand sample class

Our 1-hour on-demand sample class is a great way to preview what the new Live Online experience is like for the Beginner Python & Math for Data Science professional development course.

Gordon Dri, Data Scientist at Oracle, and instructor of the Live Online Beginner Python & Math for Data Science course, will cover a few sample topics in the on-demand class:

  1. How to setup Jupyter Notebook and begin to write basic Python code
  2. A brief overview of a fundamental math topic from the course
  3. Followed by Q&A

FAQs

Have more questions? No problem. Schedule a chat with admissions