Looking to accelerate your career in data science? Gain in-demand knowledge immediately transferrable to your work with live online data science programs, powered by Metis. 

Beginner Python & Math for Data Science

Designed for the absolute beginner looking for an introduction to the basic building blocks essential to developing data science skills. This course is for those who have little to no prior experience, or need a refresher with the fundamental Python programming and/or mathematic concepts necessary to succeed at the next level or forge new career opportunities.

 


“This course gave me a good idea of what I will be working with and what I will be doing as a data scientist. The instructor was very good and very patient. Between the use of the Jupyter Notebooks and the recorded sessions, the course has given me a breadcrumb trail to complete the mastery of each topic covered after the course is finished… I’m glad I found Metis!”

MICHAEL REEKIE

“I most liked the fantastic teachers who are passionate about the subject matter, and whom make themselves available to assist students in answering questions or providing suggestions… Thank you for the great course and providing me with more insight into understanding what baseline subjects I need to understand to begin working towards my goal of starting a data science career.”

ANTHONY LIU

Learn from world-class data science practitioners

Live online instructors bring deep industry experience and will be available to support you throughout your learning process.

Interact with instructors and classmates in real-time

Ask questions, participate in discussions and join your course Slack channel for maximum engagement, collaboration and support.

The benefit of online learning with live instruction

Log in from wherever you are to access live online classes. If you miss a class or need to refer back, recordings are available 24/7.

Overview

COURSE TOPICS:

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 OUTCOMES:

The ability to tackle courses in data science, particularly our Introduction to Data Science part-time course and full-time immersive Data Science Bootcamp.

 

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.

Course Structure and 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 visualisation. 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 visualising.

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.

Dates and Instructors

LIVE ONLINE
Special Introductory Price: $990

     14 September to 22 October  |  Mondays and Thursdays  |  6:00PM to 9:00PM AEST 

     Please click here to register your interest and we’ll let you know when the next class is open for enrolment.

ALISON COSSETTE  Instructor

Alison is a Director of Data Science in Research and Development at the NPD Group, a global market research firm.

At NPD, Alison leads data science projects focusing on classification, data imputation and customer segmentation. She is also responsible for analysing and integrating third-party data sources that support modelling initiatives for NPD’s omni-channel product, Checkout.

Alison was previously a Data Scientist in the healthcare industry after transitioning from a 10-year career in clinical care of oncology patients. Throughout her medical and analytics experience, Alison has consistently been an educator and mentor, including teaching positions at The University of Vermont Medical Centre, The Swedish Institute of Allied Health Sciences and Northwestern University.

Alison’s masters studies in Data Science were completed through Northwestern University and she is a proud alumnus of the Metis Data Science Bootcamp. Alison lives in Vermont with her husband, two young boys and an energetic chocolate Labrador named ‘Gracie’.

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 will need a Github account to gain access to the content and a Slack account to collaborate with their instructor and peers. Sign-up 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.

Course Co-designer Roberto Reif, Senior Data Scientist, Metis and Gordon Dri, Data Scientist, Oracle

Download a brochure

Please complete the form to download a brochure. We’ll also send you a free sample class so you can see what the live online experience is like for our data science courses.

Gordon Dri, Data Scientist at Oracle, and instructor of the live online Beginner Python & Math for Data Science course, will cover the following sample topics in the sample class:

 

How to set up Jupyter Notebook and begin to write basic Python code

 

A brief overview of a fundamental math topic from the course

Frequently asked questions

Anyone who is interested in data science, including individuals who enjoy working with and analysing data to solve problems. Those in data adjacency roles such as data analysts, functional analysts and data-driven decision makers are also suited to this course. Individuals who are considering a new career or looking to upskill or reskill in the data science field may find this course useful.

No, you’ll receive a certificate of completion stating you’ve completed the course.

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.

Course instructors are from the 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 job.

The course runs two nights per week over 6 weeks, totalling 36 hours of instruction.

All classes are delivered live online via Zoom. Course content is accessed via GitHub, and Slack is used to provide support, as well as facilitate collaboration with the instructor and your peers. Details on how to access these platforms will be provided in your welcome email upon enrolment.

The live online format allows you to attend class sessions from anywhere with a stable internet connection. Unlike other online options, where sessions may be pre-recorded, the live online format allows for interaction with the instructor, teaching assistant and other participants.

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.

To complete the Beginner Python and Math for Data Science course, you’ll require a computer or laptop with a stable internet connection to attend the live online classes via Zoom.

Course content is accessed via GitHub, and Slack is used to provide support, as well as facilitate collaboration with your instructor and classmates. Sign-up to these platforms is free and details on how to access them will be provided in your welcome email on enrolment.

Python is a widely used and rapidly growing open-source programming language, commonly used by data scientists, data analysts and software engineers. Unlike Excel, Python is scalable, and is better able to meet business needs by readily handling massive data sets and accommodating the demands of real-time analysis and collaboration. In addition to being immensely popular, Python is a straightforward and user-friendly programming language, making it very easy to learn.

Research shows there’s growing demand for qualified individuals for positions in the data science field. This is largely driven by the exponential growth of available data and the narrow set of specific skills required to extract value from that data. Recent estimates suggest 2.5 quintillion bytes of data are created each year, with 90% of all data in existence being created in just the last two years1.  As a result, the number of data-related job postings has surged and median salaries have risen, leading to ‘data scientist’ becoming the best job in a 2016 Glassdoor survey based on the number of job openings, salary and job satisfaction1.

External data continues to validate the demand for the types of programs Metis offers. For example:

  • According to a recent global survey, 76% of businesses plan on increasing investment in analytics capabilities over the next two years1.
  • The most common salary for data scientists in Australia is between $120,000- $140,0002.
  • The projected job growth for data scientists in Australia between 2019 and 2024 is 12.9%2.

 

1 Deloitte Access Economics, 2018, The future of work: Occupational and education trends in data science in Australia.
2
Seek, 2020, How to become a Data Scientist- Salary, Qualifications & Reviews.

Yes, you can access recordings of live sessions at any time if you’re unable to attend classes. To get the most out of your learning experience, it’s strongly advised you attend all live online classes. This ensures you can interact with your instructor and classmates, participate in discussions and ask questions.

Yes. The Beginner Python and Math for Data Science course is designed for absolute beginners with little to no experience in data science. This course is ideal for anyone who is interested in data science or enjoys working with and analysing data to solve problems. It provides an introduction to the basic Python programming and mathematic building blocks essential to developing data science skills or forging new career opportunities.