By this point, nearly everyone is aware of the profound influence that generative AI has exerted on the technology sector. This recognition is not merely a result of exaggerated claims. Generative AI has indeed delivered tangible advantages and increased productivity. While it may seem straightforward to log in to ChatGPT Plus and task DALL-E 3 with producing portraits of all states, there exists a multitude of untapped possibilities within the realm of AI for those who are well-informed.
This is where educational materials play a crucial role. In recent months, I have been highlighting a selection of high-quality courseware options that are not only free but also exceptionally valuable. Despite the abundance of individuals seeking to monetize their training services, ranging from subpar to exceptional, my focus has been on showcasing a variety of outstanding free courseware offerings.
LinkedIn Learning stands out as one of the pioneering online course providers, established nearly three decades ago by Lynda Weinman. Originally known as Lynda.com, it was later acquired by LinkedIn in 2015. Having been a subscriber to this service since its early days, I now benefit from a complimentary subscription as an alum of my graduate school. The courses offered are consistently of high quality, with instructors who are both knowledgeable and approachable.
Typically, the service is priced at \(39 per month for a monthly subscription and \)19.95 per month for an annual prepayment. Additionally, team plans are available. However, as of today, LinkedIn has made 250 AI courses accessible for free for a month, allowing everyone to engage in learning without any cost.
Key Distinctions from LinkedIn’s Standard Free Trial
This special 30-day program differs from LinkedIn’s regular 30-day free trial in several significant ways:
- No registration with LinkedIn is required.
- No credit card information is needed.
- Even if you have previously exhausted your free trial period for LinkedIn Learning, you can still enroll in these courses. Subsequently, you will retain the option to sign up for a standard 30-day LinkedIn Learning trial after completing these courses, thereby enabling a separate trial period.
I must extend my appreciation to LinkedIn for this initiative. Unlike most companies that offer freebies as a means to build a marketing database for future promotional activities, LinkedIn has chosen a different path. If you wish to learn while maintaining complete anonymity, without divulging any personal information or being subjected to future marketing endeavors, this opportunity allows for precisely that.
This transforms what initially appeared to be a typical marketing strategy into a commendable endeavor. It is now up to you to make the most of the next 30 days by absorbing as much knowledge as possible. If you are willing to sacrifice some sleep, you can acquire a wealth of knowledge at no cost.
Notable Courses I Completed
In this article, I have highlighted fourteen courses that I found particularly intriguing. Among these, my favorite—albeit with a hint of bias due to the author being a colleague—is “ChatGPT Tips for the Help Desk” by Pam Baker. Pam, a seasoned technology journalist and the author of “ChatGPT for Dummies,” delves into why chatbots are ideally suited for help desks, the integration of APIs with these technologies, and the critical importance of preventing hallucinations when deploying self-service help solutions. Furthermore, she explores various help desk scenarios, including the advantages and disadvantages of human help desk agents utilizing ChatGPT in real-time.
Also: What is an AI PC? (And should you buy one?)
I also completed the two-hour course on “Machine Learning with Python: Foundations,” which featured an exceptional instructor previously unknown to me. This course provided valuable insights into data collection and preparation for machine learning, as well as enhancing my Python programming skills, particularly in building machine learning models using Python. In just two hours, Professor Nwanganga delivered a comprehensive and engaging learning experience.
Numerous other courses cover a wide range of topics. Let’s categorize and explore some examples.
Enhancing General AI Literacy
The following courses are beneficial for professionals seeking to enhance their overall understanding of AI.
Integrating Generative AI into Business Strategy 4.7 stars (97 ratings)
Chris McKay offers a detailed guide for decision-makers on effectively understanding, evaluating, and implementing generative AI within their organizations.
Building Career Agility and Resilience in the Age of AI 4.8 stars (244 ratings)
Chris Shipley delves into reimagining one’s career to thrive in the era of AI, exploring the impact of AI technologies on work, proactive adaptation strategies, and the development of skills essential for a “future-proof career mindset.”
AI Courses Tailored for Recruiting, Finance, and Support Professionals
AI’s unique capabilities can be harnessed across various professional domains. I have selected courses tailored for recruiting, support, and finance professionals to illustrate how AI can be leveraged within specific fields.
Generative AI, Recruiting, and Talent Acquisition 4.7 stars (1,281 ratings)
Glen Cathey navigates the evolving landscape of recruiting and talent acquisition, offering insights for hiring managers and recruiting leads on integrating generative AI and automation effectively.
Leveraging Generative AI in Finance and Accounting 4.7 stars (349 ratings)
Glenn Hopper provides a comprehensive exploration of generative AI applications in finance and accounting, focusing on financial forecasting and analysis.
ChatGPT Tips for the Help Desk 4.5 stars (47 ratings)
Pam Baker covers a wide array of topics relevant to help desk managers, from strategic planning and agent scripting to self-help repositories and problem resolution using ChatGPT.
For Tech Professionals and Power Users
The following five courses cater to professionals working with large language models (LLMs) to develop or enhance AI-driven business solutions, requiring a certain level of technical proficiency.
Generative AI: Introduction to Large Language Models 4.7 stars (1,274 ratings)
Jonathan Fernandes provides an overview of key large language models developed post the release of GPT-3 by OpenAI, highlighting the contributions of each model.
ChatGPT for Web Developers 4.7 stars (362 ratings)
Sandy Ludosky introduces web developers to ChatGPT, explaining its functionality and how to utilize it for code generation using JavaScript and ReactJS.
Build Your Own GPTs (Rating not available yet)
Alina Zhang guides learners through creating custom GPTs, exploring innovative techniques and strategies to enhance prompt engineering, few-shot learning, and user intent detection.
Securing the Use of Generative AI in Your Organization 4.8 stars (85 ratings)
This course equips individuals with the knowledge and skills to navigate AI security challenges, enabling the safe integration of generative AI while safeguarding sensitive information.
Azure OpenAI: Generative AI Models and How to Use Them 4.8 stars (217 ratings)
Sammy Deprez introduces Azure OpenAI services and delves into available models, including GPT models, embedding models, codex models, and DALL-E models.
AI Courses for Python Coders
Given Python’s popularity among AI developers, the following four courses focus on integrating Python proficiency with AI applications. According to Ya Xu, VP of Engineering, Head of Data and AI at LinkedIn, skills in key programming languages like Python, Java, and SQL are among the most sought-after technical skills in the US.
Generative AI for Python Developers 4.7 stars (22 ratings)
Sandy Ludosky teaches how to leverage generative AI for developing advanced Python applications, including utilizing the OpenAI API to build customized AI assistant chatbots within applications.
Machine Learning with Python: Foundations 4.7 stars (4,060 ratings)
Frederick Nwanganga, an associate professor of analytics at the University of Notre Dame, provides a beginner-friendly introduction to machine learning and guides learners on initiating machine learning projects using Python.
SQL Server Machine Learning Services: Python 4.8 stars (494 ratings)
Adam Wilbert demonstrates the use of high-performance Python libraries and Machine Learning Services within SQL Server to streamline statistical analysis, generate visualizations, and process tabular data.
Training Neural Networks in Python 4.6 stars (219 ratings)
Eduardo Corpeño delves into the intricacies of neural networks in Python, empowering learners to understand algorithms and construct and train neural networks from scratch using Python.
Additional Free AI Training
This compilation is part of an ongoing series spotlighting free AI training opportunities. Here are four more resources:
The transformative potential of AI is undeniable, albeit with certain limitations and considerations. I highly recommend taking advantage of this wealth of free courseware while it remains accessible.
Have you engaged with any of these courses or training programs? What valuable insights have you gained? Are you considering enrolling in LinkedIn Learning’s courses? Feel free to share your thoughts and interests in the comments section below.
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