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Beginner Python & Math for Data Science

Designed for those who have little to no prior experience, or need a refresher with the fundamental Python programming and/or math concepts necessary to succeed at the next level or forge a new career.

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.

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

HAVE QUESTIONS?

Get answers to frequently asked questions. FAQs >

Dates and Instructors

LIVE ONLINE
Introductory Price: $990

     25 May to 2 July  |  Mondays and Thursdays  |  6:30PM – 9:30PM AEST

SUMMER RANKIN | Instructor

Summer is currently a lead data scientist in the Strategic Innovation Group at Booz Allen Hamilton.

She works on projects that involve a range of techniques including deep learning, NLP, anomaly detection, and performance measurement. She is the technical lead on Project Shakespeare with Dr. Roselie Bright, an Epidemiologist at the FDA where she is using machine learning and NLP techniques to identify indicators for adverse events based on free text (notes) from electronic health records.

She holds a PhD in Complex Systems and Brain Sciences and completed a postdoctoral fellowship (5 years) with Charles Limb, MD at Johns Hopkins School of Medicine where she studied musical creativity, auditory perception (fMRI) and human coordination with 1/f-type (fractal) auditory signals.

She is a proud Alumnus of the Metis Bootcamp (Chicago) where she learned how to apply and hone her academic skillset to the field of data science.

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.

Live online interactive learning

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.

Register for a free sample class

The 1-hour on-demand sample class is a great way to preview what the live online experience is like for the Beginner Python & Math for Data Science course.

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 on-demand 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

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.

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.