In the 2007 film, Shift Happens, Carl Fisch (later modified by Scott Mcleod) stated that “The top 10 in-demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”
Although the 65% figure has been debunked quite often and the data that was used during the video cannot always be verified, it is safe to say that the jobs of today, have evolved quite a bit since 2004. In addition, a lot of these fields are Global, rely a lot on technology and the use of code, like Python. In this podcast series, we will speak to professionals in the field that have jobs in industries including Fintech 3.0, Cybertechnology, Ethical AI, and Data Science
We welcome Michael Galarnyk. Michael currently teaches Python for Data Visualization for LinkedIn Learning, Data Analytics using Python for UCSD Extension, Machine Learning Fundamentals for UCSD Extension, and Machine Learning with Python for Stanford Continuing Studies. I have previously taught Essential Python for Global Knowledge and Data Science (Python) at General Assembly.
Special Guest: Michael Galarnyk.
Links:
- Python for Data Visualization — Data visualization is incredibly important for data scientists, as it helps them communicate their insights to nontechnical peers. But you don’t need to be a design pro. Python is a popular, easy-to-use programming language that offers a number of libraries specifically built for data visualization.
- Data Analytics Using Python | UC San Diego Extension — In this course, you will learn the rich set of tools, libraries, and packages that comprise the highly popular and practical Python data analysis ecosystem. This course is primarily taught via screen sharing programming videos. Topics taught range from basic Python syntax all the way to more advanced topics like supervised and unsupervised machine learning techniques.
- Machine Learning Fundamentals | UC San Diego Extension — Utilizing machine learning to apply algorithms to their data has helped companies maximize efficiencies, pursue new markets, and create new products. This trend has prompted many industries to recognize the value of machine learning, creating a high demand for knowledge in this field. Understanding the theory of how machine learning algorithms work is not only important skill for being able to apply and debug code, but also an important skill for interviewing.
- How Charts Lie: Getting Smarter about Visual Information: Cairo, Alberto: 9780393358421: Amazon.com: Books — A leading data visualization expert explores the negative―and positive―influences that charts have on our perception of truth. Today, public conversations are increasingly driven by numbers. While charts, infographics, and diagrams can make us smarter, they can also deceive―intentionally or unintentionally.
- Dogsheep — Tools for personal analytics, powered by Datasette
- PyCon 2022 — Sean & Kelly's PyCon talk: Learn Python Like a 12-year-old