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.
What you'll receive upon completion:
- Certificate of completion
- 3.3 Continuing Education Units
Dates & Instructors
Live Online
Beginner Python and Math for Data Science
March 11 to April 18
Mondays and Thursdays
6:30 - 9:30PM PST
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.
Live Online
Beginner Python and Math for Data Science
April 29 to May 16
Mon, Tues, Wed, and Thurs
6:30 - 9:30PM PST
Instructor Coming Soon
Live Online
Beginner Python and Math for Data Science
May 13 to June 17
Mondays and Thursdays
6:30 - 9:30PM CST
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.
Live Online
Beginner Python and Math for Data Science
June 24 to August 5
Mondays and Thursdays
6:30 - 9:30PM PST
Samiyeh Mahmoudian
Instructor
Samiyeh is currently a Senior Data Scientist with Intertrust, where she works on industry-leading machine learning algorithms in IOT to optimize the operation of the “vertical industry,” such as energy and insurance. With her teaching experience and knowledge, she is leading the Data Science internship program for Interturst. Samiyeh has a doctorate in Theoretical Physics from Florida State University and the National Hight Magnetic Field Laboratory. During her PhD, she worked on advanced statistical analysis to understand the nature of disordered systems—such as glasses. Prior to joining Intertrust, she was an adjunct lecturer at San Francisco State University. Teaching is her passion and she enjoys sharing her experiences with anyone willing to learn.
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?
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:
- How to setup Jupyter Notebook and begin to write basic Python code
- A brief overview of a fundamental math topic from the course
- Followed by Q&A
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FAQs
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For this course, do I need to know Python. If so, how much Python do I need to know to take this course? What version of python is used?
No, we will teach you the fundamentals of programming. The class uses Python 3.
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How much do part-time courses at Metis cost?
In-person professional development courses are $2,100. Live online professional development courses range from $1,250-$1,900.
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Can I apply tuition from my part-time course to the bootcamp?
Yes! Part-time alumni can apply the amount of tuition paid for one part-time course toward enrollment in an upcoming bootcamp upon admittance.
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Do I receive pass/fail grades on completion of a part-time course?
No, you receive a certificate of completion stating that you completed up to 36 hours of the course, accredited by ACCET (Accrediting Council for Continuing Education and Training). Hours vary by course.
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How much homework is required outside of class time?
While there is no official homework, you can expect to spend a minimum of 3 hours per week reviewing material or working on projects. The non-class time spent will depend on your background and the course itself. Each instructor will address this on the first day of class, and there will be lab/office hours outside of class during which students and the instructor can collaborate.
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Do I get career support if I take a part-time course?
No. We do not offer career support for students of these courses like we do for our bootcamp students, but you will gain access to our alumni community network of 500+ data scientists. Networking events and job opportunities are posted on a regular basis in this active digital community.
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Who are the instructors for the part-time courses? Are they bootcamp instructors? What are their backgrounds?
Our part-time course instructors come to teach at Metis from industry and have real-world experience as practitioners of data science. Please visit the respective course pages for specific information on each instructor’s background and current jobs.
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How often do Metis part-time courses meet?
Our part-time courses typically run two nights per week over the course of 6 weeks, totaling 36 hours of instruction, but this can vary. Please see the full schedule here for the most up-to-date information. We consistently add new courses, so be sure to check back routinely.
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Does Metis offer any part-time courses online?
Yes, we currently offer a rotating selection of our part-time professional development courses in a Live Online format, meaning once registered, you can login from anywhere to learn.
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What are the benefits of taking a course in a Live Online format?
The beauty of the Live Online format is that you’re taught by our industry-leading instructors live, but you can attend class sessions from literally anywhere you have an internet connection. Unlike some other online course options out there, which might consist of pre-recorded lectures, our courses allow for interaction with the instructor, assistant instructors, and other students – and because these are on a set schedule, you’ll be held accountable to actually attend, do the work, and learn the material (which is what you’re really here for anyway!).
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I took a Metis part-time course and now want to apply for the bootcamp. Does that give me a competitive edge?
It does not, simply because we evaluate each and every bootcamp applicant the same way in order to ensure fairness. However, if accepted into the bootcamp, you do have the advantage of applying the amount of one part-time course tuition toward the bootcamp tuition, so you essentially got your part-time course for free.
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How will I receive access to the curriculum?
The curriculum will be provided via Github; therefore, you must register a Github account. Sign-up for an account on their site is free, fast and easy. Github is a web-based hosting service for version control using Git.