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Accredited Professional Development Data Science Course

Beginner Python and Math for Data Science

Offered Live Online Only

Want to learn more about data science but have no idea where to start? This course is for absolute beginners looking for an introduction to the basic Python programming and mathematical principles essential to learn as a first step toward developing data science skills or a new career in the field. We will cover:

  • 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

Who the course is designed for:

For beginners who want to learn data science from scratch and have no prior experience with fundamental Python programming and math concepts. Whether you’re considering a new career in data science, you want to understand the basics in order to advance in your current career, or you want to be able to communicate more effectively with data-oriented colleagues, you’ll complete this course with a solid understanding of some of the basic skills required.  The only prerequisite is to have Python installed.

Outcomes

  • The ability to write basic Python code such as functions, data manipulation, and visualization.
  • 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.
  • Ability to tackle courses in data science, particularly our Introduction to Data Science and Statistics courses.
Have questions? Get answers to frequently asked questions. FAQs

What you'll receive upon completion:

  • Certificate of completion
  • 3.3 Continuing Education Units

Dates & Instructors

Live Online
New 2019 Pricing! $750 $1,250

Beginner Python and Math for Data Science

January 14 to February 25

Mondays and Thursdays

6:30 - 9:30PM EST

AMA with Instructor 1/8 - RSVP on Events Page

Gordon dri
Gordon Dri
Instructor

Gordon is currently a Data Scientist with Oracle. He has also worked in research at the University of Chicago's Harris School of Public Policy and Booth School of Business and interned as a quantitative analyst in commercial real estate investment at Magnolia Capital. He has a Master of Science in Analytics from the University of Chicago and a Bachelors of Applied Science and Engineering from the University of Toronto. Gordon thoroughly enjoys teaching and, in addition to course design and teaching at Metis, acted as a Teaching Assistant for Statistical Analysis, Data Mining and Linear and Non Linear Models in the MScA program at the University of Chicago

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Live Online
New 2019 Pricing! $750 $1,250

Beginner Python and Math for Data Science

February 11 to March 21

Mondays and Thursdays

6:30 - 9:30PM EST

Note: No lecture 2/14, rescheduled to 2/13. No lecture 2/18, rescheduled to 2/19.

Sergey fogelson
Sergey Fogelson
Instructor

Sergey Fogelson is the Vice President of Analytics and Measurement Sciences at Viacom. He began his career as an academic at Dartmouth College in Hanover, New Hampshire, where he researched the neural bases of visual category learning and obtained his Ph.D. in Cognitive Neuroscience. After leaving academia, Sergey got into the rapidly growing startup scene in the NYC metro area, where he has worked as a data scientist in alternative energy analytics, digital advertising, cybersecurity, finance, and media. He is heavily involved in the NYC-area teaching community and has taught courses at various bootcamps, and has been a volunteer teacher in computer science through TEALSK12. When Sergey is not working or teaching, he is probably hiking. (He thru-hiked the Appalachian trail before graduate school).

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Live Online
New 2019 Pricing! $750 $1,250

Beginner Python and Math for Data Science

March 11 to April 18

Mondays and Thursdays

6:30 - 9:30PM EST

Nathan grossman
Nathan Grossman
Instructor

As a former engineer, Nathan enjoys data science because it allows him to apply the mathematical skill set he developed designing algorithms for individual products to optimize the behavior of entire organizations. Nathan began his career developing signal processing algorithms for wireless communications at Qualcomm. He subsequently worked in data analytics for intellectual property applications, and in data science for telecom applications. Nathan is currently a data scientist at Wells Fargo, working on machine learning for FinTech applications. He holds a BS in Mechanical Engineering from the University of Illinois, an MS in Electrical Engineering from the University of Michigan, and an MBA from the University of Pennsylvania’s Wharton School, as well as certificates in data science and data analytics from UC Berkeley and UC Santa Cruz. When not working, Nathan enjoys skiing, cycling, playing tennis and spending time with his wife and three sons.

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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 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?

Professional development 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.

Earn CEUs for accredited courses.

Not only will you walk away with new data science skills and knowledge, you’ll also earn up to 3.3 Continuing Education Units (CEUs). Our courses are accredited by ACCET, who requires we maintain high standards in areas such as quality of instruction and positive student feedback.

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

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FAQs

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