Guide
30 Intro Artificial Intelligence Courses
Written By Nat Davis
Edited By Jess Feldman
Last updated on April 11, 2024
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Written By Nat Davis
Edited By Jess Feldman
Course Report strives to create the most trust-worthy content about coding bootcamps. Read more about Course Report’s Editorial Policy and How We Make Money.
Course Report strives to create the most trust-worthy content about coding bootcamps. Read more about Course Report’s Editorial Policy and How We Make Money.
Artificial intelligence (AI) has evolved over the past 70 years to learn human-like cognition and ease the workload by performing functions faster than humans in computation, perception, reasoning, learning, problem-solving, and even creativity! In 2023, AI is unavoidable in the modern workforce as tools like ChatGPT, Google Bard, and Microsoft Bing are incorporated into workflows across major industries from healthcare to transportation, manufacturing, retail, finance, insurance, and food tech. Choosing the right AI course to level up can feel daunting, so here’s a list of AI courses to support anyone interested in learning Artificial IntelIigence tools.
While there’s no doubting the immense potential for AI capabilities, there will always need to be skilled humans to help ensure its accuracy and direction. Getting familiar with machine learning, data science, and data analysis will help guide your direction to learn AI — especially if your goal is to have a career in AI! While AI technology will continue to evolve, in 2023 learning AI includes learning Python, Java, and C++; data visualization and machine learning models; and mathematics like linear algebra, data interpretation, and deep learning.
AI is not just for engineers and scientists! AI training will come in handy for creative roles like content marketers, artists, UX designers, and more! If you’re not sure where to start, AI for Everyone from deeplearning.ai through Coursera is a perfect first step to learning AI.
Work for content marketers got a lot easier when generative AI learned to write copy and personalize marketing and sales content equipped with images, videos, and text.
Software developers use generative AI to write, document, and review code.
Data scientists support the development of AI to learn patterns and correlate data, which they then generate insight from.
AI supports quality assurance (QA) testers by using image-based testing, determining to run a test script, using AI spidering, monitoring API testing, and automating tasks.
UX designers can lean on AI when analyzing user data, creating user personas, product writing, automating design workflows, adding UI elements including branding, user testing and prototyping, and helping designers move through stagnancy.
Artists are using AI to open their creative potential by generating color palettes, producing digital sculptures, expanding graphic design possibilities, producing interior designs and architecture, and creating realistic animations.
Product development is seeing a rise in AI technology as it is being used in concept development, design, prototyping, testing, and final production, as well as aiding market research and analysis and optimizing the design experience.
AI is undoubtedly easing sales as virtual assistants catered to the industry are able to alleviate tasks for human users by simplifying and optimizing the sales process.
AI is assisting the medical industry by learning diseases and chemical structures to accelerate the development of drugs. Similarly, AI is making medical processes like imaging faster and more precise.
AI is rapidly changing — while the workforce figures out how to integrate AI tools into their processes, leaders in AI provide insights on what to learn, where to learn, and what to anticipate in this exciting future. We recommend following a few leaders in the space – here are 7 of our favorites!
| Andrew Ng | Founder and CEO of Landing AI, Founder of deeplearning.ai, and Professor of Computer Science at Stanford University. Andrew also hosts AI courses on Coursera for data scientists and programmers. |
| Sequoia Professor of Computer Science at Stanford University, Fei-Fei co-founded a non-profit aimed at diversity and inclusion in AI education, research, development, and policy. She’s an expert in machine learning, deep learning, computer vision, and cognitive neuroscience. | |
| Andrej Karpathy | Senior Director of Artificial Intelligence at Tesla and a student of Dr. Fei-Fei Li! Andrej is known for training deep neural nets on large databases. |
| Kate Crawford | Senior Principal Researcher at Microsoft Research; co-founder and Director of Research at the AI Now Institute at NYU; and Visiting Professor at MIT. Kate has published many books and journals on AI’s impact on society. |
| Demis Hassabis | Co-founder and CEO of DeepMind, an AI company inspired by neuroscience. Demis started in the gaming industry with chess and video games, and is now one of the top AI leaders after his work in memory and amnesia. |
| Director of Machine Learning at Apple and formerly a research scientist at Google Brain. Ian is a former student of Andrew Ng at Stanford. | |
| Global Head of Machine Learning BD, Startups & Venture Capital at AWS. Allie is an advocate of education and diversity in AI, and the youngest-ever woman to build an AI product at IBM! |
Already using AI on the job? Let us know your go-to AI tools in the comments!
Nat Davis connects to writing to communicate stories, thoughts, ideas, and resources. When not jotting, Nat is a health coach, hiker, youth advocate, foodie, comedian, improviser, and karaoke singer.
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