How LinkedIn's free AI course made me a better Python developer

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How LinkedIn's free AI course made me a better Python developer

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By now, almost everyone knows about generative AI's impact on the tech industry. And that's not all hype: GenAI has produced genuine benefits and productivity gains. But while logging into ChatGPT Plus and asking DALL-E 3 to generate a portrait of every state is pretty easy, if a bit tedious, there's a great deal more you can do with AI – if you know how.
Also: ChatGPT can now read its responses aloud – how to listen to them
And that's where learning resources come in. Over the past few months, I've been spotlighting courseware offerings that are both free and good. Sure, a ton of folks are trying to take your money in return for training ranging from mediocre to great. But rather than encouraging you to pay out your hard-earned Benjamins, I've been spotlighting a bunch of really excellent free courseware offerings.
LinkedIn Learning is one of the original online courseware providers. Started almost 30 years ago by Lynda Weinman, the site was known as Lynda.com until it was acquired by LinkedIn in 2015. I've been a subscriber to the service since the early days, and now I get my subscription as an alumnus of my grad school. LinkedIn Learning's courses are almost all solid and its teachers are clear and friendly.
Also: The best AI image generators: Tested and reviewed
Normally, the service costs $39/mo if you sign up to pay month-by-month, and $19.95/month if you prepay for a year. There are also team plans. However, as of today, LinkedIn is unlocking 250 AI courses for a month, so everyone can learn for free.
This special 30-day program differs from LinkedIn's 30-day free trial in several important ways:
I have to give a big shout-out to LinkedIn for this offering. Normally, companies offer free loss-leaders to users as a way to gather a mailing list for later promotion. LinkedIn isn't doing that. If you want to remain completely anonymous, not give up any of your personal details, and not get sold to later down the line, you can!
Also: How to add a new credential to your LinkedIn profile
That turns this from what I originally thought was just another marketing scheme into full-on good work. It's up to you to cram as many courses as you can into the next 30 days, but if you can give up enough sleep, you can learn a lot for free.
In this article, I've spotlighted 14 of the courses I think are most interesting. My favorite (although I'm partial because the author is a colleague) has to be the ChatGPT Tips for the Help Desk by Pam Baker. A seasoned technology journalist, Pam is also the author of ChatGPT for Dummies. She knows her stuff.
I took the full course. In about an hour and a half, she covers not only why a chatbot is ideally suited for a help desk, but also how to use APIs to integrate the two technologies. She goes into an important deep dive about how to prevent hallucinations, which is critical if you want to deploy self-service help solutions to customers. And she explores a wide number of help desk scenarios, including the pros and cons of human help desk agents using ChatGPT in real-time.
Also: What is an AI PC? (And should you buy one?)
I also took the two-hour Machine Learning with Python: Foundations course, which had a great instructor — Prof. Frederick Nwanganga — who was previously unknown to me. I have to hand it to LinkedIn. They choose people who know how to teach.
I learned a lot in this course, especially about how to collect and prepare data for machine learning. I also was able to stretch my Python programming knowledge, specifically about how a machine learning model can be built in Python. In just two hours, I felt like I got a friendly and comprehensive brain dump.
There are many other helpful courses. Let's break them down into categories and look at some examples.
These two are courses that any professional can take to improve understanding of AI overall.
Integrating Generative AI into Business Strategy
4.7 stars (97 ratings)
In this course, Chris McKay presents a comprehensive guide for decision-makers to understand, assess, and implement generative AI effectively in their organization.
Building Career Agility and Resilience in the Age of AI
4.8 stars (244 ratings)
In this course, Chris Shipley examines how you can reimagine your career to adapt and find success in the age of AI. Chris takes you through AI technologies and how they may impact work, ways to proactively adapt to these technologies, and skills to develop a "future-proof career mindset."
AI has some very special capabilities that can be applied in a wide range of professional fields. I chose three — recruiting, support, and finance — to show you how you can learn AI in the context of your profession.
Generative AI, Recruiting, and Talent Acquisition
4.7 stars (1,281 ratings)
Join Glen Cathey as he explores what's driving change in the world of recruiting and talent acquisition, and what's likely to happen in the future as generative AI and automation ripples across the space. Glen offers advice on navigating this complex, ever-evolving space as a hiring manager or recruiting lead, with tips on evaluating possible vendor solutions, incorporating new cutting-edge tools, and more.
Leveraging Generative AI in Finance and Accounting
4.7 stars (349 ratings)
This course provides a comprehensive exploration of generative AI in finance and accounting. Instructor Glenn Hopper covers the fundamental concepts, models, ethical considerations, and practical applications of generative AI, with a focus on financial forecasting and analysis.
ChatGPT Tips for the Help Desk
4.5 stars (47 ratings)
In this course, Pam Baker covers everything from using ChatGPT to help with strategic planning, prompt engineering, and agent scripting, to self-help repositories and problem resolution, as well as other topics of high interest to help desk managers.
I chose this set of five courses for professionals who need to work with large language models (LLMs) to build or modify AI-powered business investments. You will need some serious geek cred as a prerequisite.
Generative AI: Introduction to Large Language Models
4.7 stars (1,274 ratings)
In this course, Jonathan Fernandes walks you through the key LLMs developed since OpenAI first released GPT-3, as well as the key contributions of each of these LLMs.
ChatGPT for Web Developers
4.7 stars (362 ratings)
Join Sandy Ludosky for an introduction to ChatGPT for web developers. Explore the basics of how ChatGPT works and how to start using it to generate code. Learn to converse with the ChatGPT UI to create fully realized web applications using JavaScript and ReactJS.
Build Your Own GPTs
(So new it doesn't have a rating)
Join data scientist Alina Zhang as she creates three custom GPTs. Alina dives into innovative techniques, including the Pentagram framework for prompt engineering, chain-of-thought, few-shot learning, and user intent detection. She also provides strategies to safeguard against prompt injection attacks.
Securing the Use of Generative AI in Your Organization
4.8 stars (85 ratings)
This course equips you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying your organization's digital resilience.
Azure OpenAI: Generative AI Models and How to Use Them
4.8 stars (217 ratings)
In this course, Sammy Deprez introduces you to Azure OpenAI services and dives into the available models, including GPT models, embedding models, codex models, and DALL-E models.
Python is one of the most popular languages among AI developers. Here I look at four courses that can help you integrate your Python knowledge with AIAccording to Ya Xu, VP of engineering and head of data and AI at LinkedIn, "Skills in key programming languages commonly used in the development of AI – Python, Java, and SQL – rank among the top five most sought-after skills on the technical side in the US."
Generative AI for Python Developers
4.7 stars (22 ratings)
Join Sandy Ludosky to learn how to use generative AI to create next-generation Python applications, including the OpenAI API, which allows you to build and customize your own AI assistant chatbot directly within an application.
Machine Learning with Python: Foundations
4.7 stars (4,060 ratings)
In this course, University of Notre Dame associate professor of analytics Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via Python.
SQL Server Machine Learning Services: Python
4.8 stars (494 ratings)
Adam Wilbert shows how to use high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data.
Training Neural Networks in Python
4.6 stars (219 ratings)
This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, giving learners a chance to tap into the makings of algorithms and the steps needed to build and train their own neural networks from scratch using Python.
This article is the latest in my ongoing series of free AI training spotlights. Here are four more:
I am convinced that AI is becoming a game-changer — but with limits and caveats. Do avail yourself of this cornucopia of free courseware while it's available.
Have you taken any courses or used any of these training programs? What did you learn? Are you thinking about taking LinkedIn Learning's courses? Which ones interest you most? Let us know in the comments below.
You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter on Substack, and follow me on Twitter at @DavidGewirtz, on Facebook at Facebook.com/DavidGewirtz, on Instagram at Instagram.com/DavidGewirtz, and on YouTube at YouTube.com/DavidGewirtzTV.

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