Since ChatGPT proved a consumer hit, a gold rush has set off for AI in Silicon Valley. Investors are intrigued by companies promising generative AI will transform the world, and companies seek workers with the skills to bring them into the future. The frenzy may be cooling down in 2024, but AI skills are still hot in the tech market.

Looking to join the AI industry? Which route into the profession is best for each individual learner will depend on that persons current skill level and their target skill or job title.

When assessing online courses, we examined the reliability and popularity of the provider, the depth and variety of topics offered, the practicality of the information, the cost and the duration. The courses and certification programs vary a lot, so choose the options that are right for each person or business.

They are listed in order of skill level and, within the skill level categories, alphabetically. In most cases, each provider offers multiple courses in different aspects of generative AI. Explore these generative AI courses to see which might fit the right niche.

A name learners are likely to see on AI courses a lot is Andrew Ng; he is an adjunct professor at Stanford University, founder of DeepLearning.AI and cofounder of Coursera. Ng is one of the authors of a 2009 paper on using GPUs for deep learning, which NVIDIA and other companies are now doing to transform AI hardware. Ng is the instructor and driving force behind AI for Everyone, a popular, self-paced course more than one million people have enrolled. AI for Everyone from Coursera contains four modules:

For individuals, a Coursera account is $49-$79 per month with a 7-day free trial, depending on the course and plan. However, the AI for Everyone course can be taken for free; the $79 per month fee provides access to graded assignments and earning a certificate.

Coursera states the class takes six hours to complete.

This course has no prerequisites.

Are you a C-suite leader looking to shape your companys vision for generative AI? If so, this non-technical course helps business leaders build a top-down philosophy around generative AI projects. It could be useful for sparking conversation between business and technical leaders.

Free if completed within the Coursera 7-day trial. Otherwise, a Coursera account is $49-$79 per month, depending on the course and plan.

This course takes about one hour.

There are no prerequisites for this course.

This is a well-reviewed beginner course that sets itself apart by approaching AI holistically, including its practical applications and potential social impact. It includes hands-on exercises but doesnt require the learner to know how to code, making it a good mix of practical and beginner content. Datacamps Understanding Artificial Intelligence course is particularly interesting because it includes a section on business and enterprise. Business leaders looking for a non-technical explanation of infrastructure and skills they need to harness AI might be interested in this course.

This course can be accessed with a DataCamp subscription, which costs $25 per person per month, billed annually. Educators can get a group subscription for free.

Including videos and exercises, this course lasts about two hours.

This course has no prerequisites.

Google Clouds Introduction to Generative AI Learning Path covers what generative AI and large language models are for beginners. Since its from Google, it provides some specific Google applications used to build generative AI: Google Tools and Vertex AI. It includes a section on responsible AI, inviting the learner to consider ethical practices around the generative AI they may go on to create. Completing this learning path will award the Prompt Design in Vertex AI skill badge.

Another option from Google Cloud is the Generative AI for Developers Learning Path.

This course is free.

The path technically contains 8 hours and 30 minutes of content, but some of that content is quizzes. The time it takes for each individual to complete the path may vary.

The path has no prerequisites.

Since this course is taught by an IBM professional, it is likely to include contemporary, real-world insight into how generative AI and machine learning are used today. It is an eight-hour course that covers a wide range of topics around artificial intelligence, including ethical concerns. Introduction to Artificial Intelligence includes quizzes and can contribute to career certificates in a variety of programs from Coursera.

Free if completed within the 7-day Coursera free trial, or $49-$79 per month afterward, depending on the course and plan. Financial aid is available.

Coursera estimates this course will take about eight hours.

There are no prerequisites for this course.

AWS offers a lot of AI-related courses and programs, but we chose this one because it combines fundamentals the first two courses in the developer kit with hands-on knowledge and training on specific AWS products. This could be very practical for someone whose organization already works with multiple AWS products but wants to expand into more generative AI products and services. This online, self-guided kit includes hands-on labs and AWS Jam challenges, which are gamified and AI-powered experiences.

The AWS Generative AI Developer Kit is part of the AWS Skill Builder subscription. AWS Skill Builder is accessible with a 7-day trial, after which it costs $29 per month or $449 per year.

The courses take 16 hours and 30 minutes to complete.

This course is appropriate for professionals who have not worked with generative AI before, but it would help to have worked within the AWS ecosystem. In particular, Amazon Bedrock is discussed at such a level that it would be beneficial to have completed the course AWS Technical Essentials or have comparable real-world experience.

Harvards online professional certificate combines the venerable universitys Introduction to Computer Science course with another course tailored to careers in AI: Introduction to Artificial Intelligence with Python. This certification is suitable for people who want to become software developers with a focus on AI. This course is self-paced, and students will receive pre-recorded instruction from Harvard University faculty.

Both courses together cost $466.20 as of the time of writing; this is a discounted price from the usual $518. Learners can take both courses in the certification for free, but the certification itself requires a fee.

These courses are self paced, but the estimated time for completion is five months at 7-22 hours per week.

There are no prerequisites required, although a high-school level of experience with programming basics would likely provide a solid foundation. The Introduction to Computer Science course covers algorithms and programming in C, Python, SQL and JavaScript, as well as CSS and HTML.

MIT has played a leading role in the rise of AI and the new category of jobs it is creating across the world economy, the description of the program states, summing up the educational legacy behind this course. MITs AI and machine learning certification course for professionals is taught by MIT faculty who are working at the cutting edge of the field.

This certification program is comparable to a traditional college course, and that level of commitment is reflected in the price.

If a learner completes at least 16 days of qualifying courses, they will be eligible to receive the certificate. Courses are typically taught June, July and August online or on MITs campus.

There is an application fee of $325. The two mandatory courses are:

The remaining required 11 days can be composed of elective classes, which last between two and five days each and cost between $2,500 and $4,700 each.

16 days.

The Professional Certificate Program in Machine Learning & Artificial Intelligence is designed for technical professionals with at least three years of experience in computer science, statistics, physics or electrical engineering. In particular, MIT recommends this program for anyone whose work intersects with data analysis or for managers who need to learn more about predictive modeling.

Completion of the academically rigorous Stanford Artificial Intelligence Professional Program will result in a certification. This program is suitable for professionals who want to learn how to build AI models from scratch and then fine-tune them for their businesses. In addition, it helps professionals understand research results and conduct their own research on AI. This program offers 1 to 1 time with professionals in the industry and some flexibility learners can take all eight courses in the program or choose individual courses.

The individual courses are:

The Stanford Artificial Intelligence Professional Program costs $1,750 per course. Learners who complete three courses will earn a certificate.

Each course lasts 10 weeks at 10 to 15 hours per week. Courses are held on set dates.

Interested professionals can submit an application; applicants are asked to prove competence in the following areas:

Udacitys Artificial Intelligence Nanodegree program equips graduates with practical knowledge about how to solve mathematical problems using artificial intelligence. This class isnt about generative AI models; instead, it teaches the underpinnings of traditional search algorithms, probabilistic graphical models, and planning and scheduling systems. Learners who complete this course will gain experience in working with the types of algorithms used in the real world for:

This course costs $249 per month paid monthly or $846 for the first four months of the subscription, after which it will cost $249 per month.

This course lasts about three months.

Learners in this course should have a background in programming and mathematics. The following skills are recommended:

Whether it is worth taking an AI course depends on many factors: the course, the individual and the job market. For instance, getting an AI-focused certification might contribute to getting a salary increase or making a career change. AI courses could help someone learn AI skills that might be a good fit for their abilities, or could be the first step toward a lucrative and life-long career. Educating oneself in a contemporary topic can always have some benefits in terms of practicing new skills.

Some introductory AI courses do not require coding; however, AI is a relatively complex topic in computing, and practitioners will need some programming skills as they progress to more advanced courses and learn how to build and deploy AI models. Most likely, intermediate learners need to be comfortable working in Python.

SEE: Help your business by becoming your own IT expert. (TechRepublic Academy)

Some of these courses and certifications include education in basic programming and computer science. More advanced courses and certifications will require learners to already have a college-level knowledge of calculus, linear algebra, probability and statistics, as well as coding.

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The 10 Best AI Courses That Are Worth Taking in 2024 - TechRepublic

COLORADO SPRINGS The National Reconnaissance Office, the secretive U.S. intelligence agency responsible for operating the countrys spy satellites, is developing a more diverse fleet of satellites alongside an overhaul of its ground systems.

Troy Meink, principal deputy director of the NRO, said the agency is looking to develop a more diverse satellite architecture, including smaller and more maneuverable models, to improve its intelligence gathering across a wider range of orbits and mission profiles.

We are pushing the boundaries to ensure we stay on the leading edge of innovation, Meink said April 9 in a keynote speech at the 39th Space Symposium. Over the next decade, we will continue to increase the number of satellites operating across multiple orbits, not just large systems that are the traditional hallmark of the NRO, but also smaller proliferated systems.

In parallel with the changes to its space-based systems, the NRO is also overhauling its satellite ground architecture, investing heavily in new technologies like artificial intelligence (AI) and machine learning to help process the flood of data coming from its expanding satellite network.

Expanding our overhead architecture will provide greater revisit rates, increased coverage, and more timely delivery of information, Meink said. This will make our collection more agile, eliminate single points of failure and will make our constellations more resilient.

Ground systems

A more diverse space architecture will allow the NRO to collect an order of magnitude more data, he said. So this means ground operations must evolve as well. I think this is actually one of the biggest challenges we face. Its not the bits that matter. Its how the bits get organized into useful information thats important.

The NROs push to modernize its ground systems started several years ago, said Joshua Perrius, senior vice president of Booz Allen Hamilton. The company is a support contractor to the NRO for ground systems modernization.

The goal is more automated tasking and collection based on data models and less on human planned activities, Perrius told SpaceNews.

The NRO is seeking more advanced data processing and exploitation capabilities on the ground to make sense of all the data its collecting, he said. They have to be able to rapidly task, re-task, and exploit data from a more diverse and resilient constellation, while also leveraging the latest AI and automation tools, said Perrius.

He said AI and machine learning algorithms can help to identify critical information and generate actionable intelligence much faster than traditional methods.

While the specific details of the NROs plans are classified, Perrius noted, this shift towards a more diverse satellite fleet and AI-powered ground systems signifies a major transformation for the intelligence agency.

The NROs fleet includes imaging satellites that take high-resolution pictures of the Earths surface, signals intelligence satellites that intercept and collect electronic communications, and others that gather information about objects by analyzing radio frequencies and other emissions.

Access to hostile territory

Millions of people count on us everyday, Meink said at the Space Symposium. Civilian customers depend on space collection to assist them with natural disasters, help predict climate change, and help relief agencies determine how and where to deliver humanitarian aid.

The Department of Defense and the intelligence community, he added, depend on the NRO capabilities, for example, for geolocation data and high-resolution imagery. The NRO systems are often the only tools able to access hostile territory or rugged terrain so we can collect critical information.

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NRO eyes diverse satellite fleet and AI-powered ground systems in modernization push - SpaceNews

Aboard is not an easy app to explain. It used to be easier: at first, it was a way to collect and organize information Trello meets Pinterest meets that spreadsheet full of links you use to plan your vacation. The companys founders, Paul Ford and Rich Ziade, are two longtime web developers and app creators (and, in Fords case, also an influential writer about the web) who previously ran a well-liked agency called Postlight. They did a bunch of interesting work on parsing websites to pull out helpful information, and they built a handy visual tool for displaying it all. People love to save links, Ziade says, and we love to make those links beautiful when they come in. Simple!

But now Im sitting here in a co-working space in New York City, a few minutes after an earthquake hit and a few days before Aboards biggest launch yet, and Ziade is showing me something very different. He opens up a beta version of the app and clicks a button, and after a second, the page begins to change. A database appears out of nowhere, with a bunch of categories Year, Title, Genre, and more that start to populate with a number of well-known movie titles. The board, as Aboard calls it, titles itself Movie Night. With one click, Ziade just built and populated a way to track your viewing habits.

Maybe the best way to explain the new Aboard is not as a Pinterest competitor but as a radical redesign of ChatGPT. When Ziade made that board, all he was really doing was querying OpenAIs GPT-3.5. The companys chatbot might have returned some of the same movies, but it would have done so with a series of paragraphs and bullet points. Aboard has built a more attractive, more visual AI app and has made it so you can turn that app into anything you want.

Ziade and Ford imagine three main things you might do with Aboard. The first, Organize, is closest to the original vision: ask the tool for a bunch of things to do in Montreal this summer, and itll populate a board with some popular attractions and restaurants. Ask Aboard to meal plan your week, and itll create a board segmented by day and by meal with nicely formatted recipes. The second, Research, is similar but a little more exploratory: ask Aboard to grab the most interesting links about African bird species, and itll dump them all into place for you to peruse at your leisure.

Like any AI product right now, this is sometimes cooler in theory than in reality. When I ask Ziade to make a board with important tech moments from 2004, it pulls a bunch of them into separate cards: Googles IPO, the launch of Gmail, the iPod Mini launch. And then the iPod Mini launch again and then another time and then three more times after that. Ziade and Ford both laugh and say this is the stuff they see all the time. A few times, a demo just fails, and each time, Ford says something to the effect of Yeah, that just happens when you ping the models. But he says its also getting better fast.

The third use case, which Aboard calls Workflow, is where Aboard figures its true business lies. Ziade does another demo: he enters a prompt into Aboard, asking it to set up a claims tracker for an insurance company. After a few seconds, he has a fairly straightforward but useful-looking board for processing claims, along with a bunch of sample cards to show how it works. Is this going to be perfect and powerful enough for an insurance company to start using as is? No. But its a start. Ford tells me that Aboards job is to build something good enough but also not quite good enough if the app can work just well enough to get you to customize it the rest of the way to fit your needs, thats the goal.

An Aboard board can be a table, a list, a gallery, and more

This is ultimately a very business-y use case and puts Aboard in loose competition with the Airtables and Salesforces of the world. Ziade and Ford are upfront about this. We want to be in professional settings, Ford says, thats a real thing were aiming for. Doesnt have to be for big enterprise, but definitely small teams, nonprofits, things like that. He figures Aboard can sell to companies by saving them a bunch of time and meetings spent figuring out how to organize data and just get them started right away. An Aboard board can be a table, a list, a gallery, and more; its a pretty flexible tool for managing most kinds of data.

I have no particular business use for Aboard, but Ive been testing the app for a while, and its a really clever way to redesign the output of a large language model. Particularly when its combined with Aboards ability to parse URLs, it can quickly put together some really useful information. Ive been saving links for months as I plan a vacation, and I had Aboard build me a project planner for managing a big renovation of my bathroom. (Its all very exciting stuff.)

Just before Aboards AI launch, I tried building another board: I prompted the AI to create a board of Oscar-winning movies, with stacks for each movie genre and tags for Rotten Tomatoes scores, and Aboard went to work. It came back with stacks (Aboards parlance for sub-lists) for six different movie genres, tags for various score ranges, plus runtimes, posters, and Rotten Tomatoes links for each flick. Were all the movies it selected Best Picture winners? Nope! Did it get the ratings right, like, ever? Nope! But it still felt like a good start and Aboard always gives you the option to delete the sample cards it generates and just start from scratch.

Aboard is just one of a new class of AI companies, the ones that wont try to build Yet Another Large Language Model but will instead try to build new things to do with those models and new ways to interact with them. The Aboard founders say they ultimately plan to connect to lots of models as those models become, in some cases, more specialized and, in others, more commoditized. In Aboards case, they want to use AI not as an answer machine but as something like a software generator. We still want you to go to the web, Ford says. We want to guide you a bit and maybe kickstart you, but were software people and we think the ability to get going really quickly is really, really interesting. The Aboard founders want AI to do the work about the work, so you can just get to work.

See more here:

Aboards AI-powered bookmarking and project app is a new spin on a chatbot - The Verge

Microsoft recently announced the creation of Microsoft AI, a newly formed organization to help advance our consumer AI products and research, including Copilot. Building on that news, Im thrilled to share that Microsoft AI is opening a new AI hub in the heart of London. Microsoft AI London will drive pioneering work to advance state-of-the-art language models and their supporting infrastructure, and to create world-class tooling for foundation models, collaborating closely with our AI teams across Microsoft and with our partners, including OpenAI.

The new AI hub will be led by Jordan Hoffmann, an exceptional AI scientist and engineer. Prior to joining Microsoft AI, Hoffmann distinguished himself as an AI pioneer at Inflection and DeepMind, based in London. Hoffmann will be joined by a talented group of Microsoft AI team members based in our London Paddington office.

There is an enormous pool of AI talent and expertise in the U.K., and Microsoft AI plans to make a significant, long-term investment in the region as we begin hiring the best AI scientists and engineers into this new AI hub.

In the coming weeks and months, we will be posting job openings and actively hiring exceptional individuals who want to work on the most interesting and challenging AI questions of our time. Were looking for new team members who are driven by impact at scale, and who are passionate innovators eager to contribute to a team culture where continuous learning is the norm.

This is great news for Microsoft AI and for the U.K. As a British citizen, born and raised in London, Im proud to have co-founded and built a cutting-edge AI business here. Im deeply aware of the extraordinary talent pool and AI ecosystem in the U.K., and Im excited to make this commitment to the U.K. on behalf of Microsoft AI. I know through my close work with thought leaders in the U.K. government, business community and academia that the country is committed to advancing AI responsibly and with a safety-first commitment to drive investment, innovation and economic growth. Our decision to open this hub in the U.K. reflects this ambition.

The Microsoft AI London hub adds to Microsofts existing presence in the U.K., including the Microsoft Research Cambridge lab, home to some of the foremost researchers in the areas of AI, cloud and productivity. At the same time, it builds off Microsofts recently announced 2.5 billion investment to upskill the U.K. workforce for the AI era and to build the infrastructure to power the AI economy, including our commitment to bring 20,000 of the most advanced GPUs to the country by 2026.

Stay tuned for more updates as we continue to push the boundaries of whats possible with AI and extend the benefits to every person and organization across the U.K.

Tags: AI, Microsoft AI

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Announcing new Microsoft AI Hub in London - The Official Microsoft Blog - Microsoft

Artificial intelligence (AI) has gained massive popularity over the past year. There is huge interest in AI stocks and every investor is looking for an opportunity to double their money. Nvidia(NASDAQ:NVDA) is a leader in the space and has already made investors rich but many under-the-radar AI stocks can outshine Nvidia.

The global AI market is expected to grow at a 15.83% compound annual growth rate by 2030 and reach amarket volume of $738.80 billion. This means investors have a massive opportunity to benefit from the rising adoption of AI. Nvidia is an expensive stock today, but if you are looking for reasonably priced under-the-radar AI stocks, here are the emerging leaders who could become hot property in the coming months.

Source: Ascannio / Shutterstock.com

At one time, Palantir(NYSE:PLTR) wasnt an investor favorite due to its secrecy. However, the company has gained massive popularity with its AI prowess and artificial intelligence platform (AIP), which is a big hit among companies.

It held boot camps to enable firms to understand how AIP works and there is a massive backlog of boot camps, showing the growing popularity of Palantirs AI product. Up 190% in the year and 48% year-to-date, PLTR stock is trading at $24 and looks undervalued to me.

The U.S. army has chosen Palantir to builda next-generation targeting systemwith a $178 million deal. It already has a strong presence in the defense industry, and Palantirs solid history of exceptional performance makes it an obvious choice for government contracts. However, it has also grown the commercial business by32% year-over-yearin the fourth quarter.

The AI industry is growing, and Palantir could be the next Nvidia. Analysts love the stock and have a positive rating. Wedbush analyst Dan Ives has a price target of $35 and calls it the Lionel Messi of AI. Further,Brian Stutland, a portfolio manager with Equity Armor Investments, considers Palantir a promising AI investment with a price target of $37, a 57% rise from the current level.

Source: JHVEPhoto / Shutterstock.com

Investors have constantly compared Nvidia and Advanced Micro Devices(NASDAQ:AMD). Nvidia has moved ahead in the race, but AMD isnt the one to sit back and watch. The stock has been on a tear since 2023 but is still up 29% YTD and 87% in the year.

Trading at $179, the stock is a solid buy before it starts to soar higher. While you might not see a rally or explosive gains, it will steadily progress. Investors have begun to give up on the stock, but it is too soon. AMD has the potential to bounce back.

The company has launched MI300X, which it believes is the worlds fastest AI hardware, and some of the biggest organizations in the world use its GPUs. Its fourth-quarter results were proof that the company is gaining strength. It saw a 10% YOY rise in sales and a 62% surge in personal computer sales in the quarter.

Several companies in the industry are looking for low-cost alternatives, and this is where AMD chips can win over Nvidia. The PC market is anticipated to improve in the coming months as the demand for AI-enabled PCs will rise. This could work as a catalyst for AMD stock.

KeyBanc analysthas an overweight rating for the stock with a price target of $270, while Melius Researchanalyst has a price target of $265 with a buy rating.

Source: Sundry Photography / Shutterstock.com

ServiceNow(NYSE:NOW) stock is unstoppable, soaring 71% in the year and 11% YTD. Trading at $767, the stock isnt cheap, but it is on its way to becoming the next Nvidia. The company offers solutions to organizations to handle their workforce and customer experience.

It uses AI and workflow management tools that help identify bottlenecks that are impacting the completion of tasks. The company has already signed a partnership with Nvidia to develop AI solutions.

ServiceNow will adopt the latest AI systems of Nvidia to enhance its platform, and Nvidia will expand the services offered by ServiceNow. This means the company will continue to benefit as long as Nvidia keeps growing.

Fundamentally, the company has impressed investors and reported an EPS of $3.11 in the fourth quarter. It beat analyst expectations with a revenue of $2.4 million, up 26% YOY. One of the most important metrics, the subscription revenue, was up 27% in the quarter to hit $2.3 billion, and it closed 168 deals worth $1 million or more in the quarter. This is higher than the 103 deals closed by Palantir.

ServiceNow is trading at a premium, but I believe the first-quarter results will be impressive and could drive the stock higher. There is no stopping the stocks rally.

On the date of publication, Vandita Jadeja did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Vandita Jadeja is a CPA and a freelance financial copywriter who loves to read and write about stocks. She believes in buying and holding for long term gains. Her knowledge of words and numbers helps her write clear stock analysis.

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3 Under-the-Radar AI Stocks That Could Outshine Nvidia - InvestorPlace