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Generative AI Certification Test: Our New Launch With Activeloop
Artificial Intelligence   Latest   Machine Learning

Generative AI Certification Test: Our New Launch With Activeloop

Last Updated on September 2, 2024 by Editorial Team

Author(s): Towards AI Editorial Team

Originally published on Towards AI.

Towards AI, together with our partners at Activeloop and Intel Disruptor Initiative, was one of the first organizations to pioneer high-quality, production-oriented GenAI courses, namely our marquee LangChain & Vector Databases in Production, Training & Fine-Tuning LLMs, as well as Retrieval Augmented Generation for Production with LlamaIndex and LangChain courses.

One year, and tens of thousands of professionals educated later, we’ve noticed one pattern: a lot of people call themselves “AI Engineers.” In fact, there are 47,000 of them on LinkedIn. But can they build AI systems that work in the real world? Because that’s the real test!

So, we’ve created a challenge. We’re calling it the ‘Impossible’ GenAI Test. It’s tough — only about 1 in 20 people pass on their first try.

What are the Topics of the Generative AI Certification Test?

What’s it all about? Well, it covers the 6 major topics of generative AI:

  • Foundational Knowledge
  • Retrieval Augmented Generation
  • Model Training & Fine-tuning
  • Observability & Evaluation
  • Model Inference & Deployment
  • Ethics & Compliance

You’ll have 40 minutes to respond to 24 questions across these knowledge areas. Our questions come from a larger bank so they do not repeat, and vary in difficulty, with more points gained based on the complexity of the question you answer.

You can take the test now, entirely for free here.

Why Did We Create the Generative AI Certification Test?

Because as AI keeps growing, we need people who can do more than just talk about it. We need folks who can roll up their sleeves and make AI work in the real world.

This test is our way of raising the bar. It’s for those who want to prove they’re not just following the AI trend, but leading it.

To address that, we’ve teamed up with top AI minds, Intel Disruptor Initiative, and TowardsAI to craft the Impossible GenAI Test. Only one in 20 test takers succeeds. Do you think it can be you?

What Questions Will Be Asked in the Generative AI Certification Test?

Each section in this Generative AI Certification test presents four randomly selected questions, ensuring a unique challenge every time. It will test everything from your deep understanding of how chunking impacts downstream solutions, to deciding on what would be the most cost-efficient solution in a case study, to what legal ramifications does building GenAI applications have in the US vs EU.

We know it’s tough — that’s the point. As GenAI becomes more prevalent, it’s critical to grasp both the fundamentals and the complexities of deploying AI in production environments. This test isn’t just an assessment; it’s a learning tool to prepare you for real-world AI challenges.

We encourage you to take the test and invite your colleagues and friends to do the same. It’s a great way to benchmark your skills and knowledge against peers in the field.

Looking ahead, we plan to introduce company leaderboards as we gather more data. This will allow organizations to gauge their collective AI expertise and identify areas for growth.

To sum up, here’s what Arijit Bandyopadhyay from Intel Corporation had to say about the initiative, developed jointly by Activeloop and the Intel Disruptor Initiative:

“AI technologies advance rapidly, so The Impossible GenAI Test is a much-needed tool for identifying top talent. It cuts through the noise, enabling executives to see if their team not only commands GenAI fundamentals, but also excels in tackling its complex production challenges. At Intel, we see this tool as vital for identifying GenAI talent capable of transforming cutting-edge concepts into scalable real-world solutions, driving responsible AI adoption across industries.”

— Arijit Bandyopadhyay, CTO — Enterprise Analytics & AI, Head of Strategy and M&A — Enterprise & Cloud (CSV Group) at Intel Corporation

And finally, this is what Louie, our CEO, had to say about the test:

‘TowardsAI has reached over 400,000 inquisitive members of the AI developer community with our tutorials and courses, many of whom strive to improve their knowledge day by day. This GenAI Test is a crucial tool for AI engineers to self-reflect on their journey, and uncover what they don’t know about GenAI.

We are looking forward to having our community members join the challenge and test their GenAI aptitude and readiness!’

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

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} strongTag.remove(); }); }); } removeStrongFromHeadings(); "use strict"; window.onload = () => { /* //This is an object for each category of subjects and in that there are kewords and link to the keywods let keywordsAndLinks = { //you can add more categories and define their keywords and add a link ds: { keywords: [ //you can add more keywords here they are detected and replaced with achor tag automatically 'data science', 'Data science', 'Data Science', 'data Science', 'DATA SCIENCE', ], //we will replace the linktext with the keyword later on in the code //you can easily change links for each category here //(include class="ml-link" and linktext) link: 'linktext', }, ml: { keywords: [ //Add more keywords 'machine learning', 'Machine learning', 'Machine Learning', 'machine Learning', 'MACHINE LEARNING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ai: { keywords: [ 'artificial intelligence', 'Artificial intelligence', 'Artificial Intelligence', 'artificial Intelligence', 'ARTIFICIAL INTELLIGENCE', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, nl: { keywords: [ 'NLP', 'nlp', 'natural language processing', 'Natural Language Processing', 'NATURAL LANGUAGE PROCESSING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, des: { keywords: [ 'data engineering services', 'Data Engineering Services', 'DATA ENGINEERING SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, td: { keywords: [ 'training data', 'Training Data', 'training Data', 'TRAINING DATA', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ias: { keywords: [ 'image annotation services', 'Image annotation services', 'image Annotation services', 'image annotation Services', 'Image Annotation Services', 'IMAGE ANNOTATION SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, l: { keywords: [ 'labeling', 'labelling', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, pbp: { keywords: [ 'previous blog posts', 'previous blog post', 'latest', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, mlc: { keywords: [ 'machine learning course', 'machine learning class', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, }; //Articles to skip let articleIdsToSkip = ['post-2651', 'post-3414', 'post-3540']; //keyword with its related achortag is recieved here along with article id function searchAndReplace(keyword, anchorTag, articleId) { //selects the h3 h4 and p tags that are inside of the article let content = document.querySelector(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); 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mlclinks = document.querySelectorAll(`#${c.id} .entry-content a.mlc-link`); llinks = document.querySelectorAll(`#${c.id} .entry-content a.l-link`); pbplinks = document.querySelectorAll(`#${c.id} .entry-content a.pbp-link`); //sending the anchor tags list of each article one by one to remove extra anchor tags removeLinks(dslinks); removeLinks(mllinks); removeLinks(ailinks); removeLinks(nllinks); removeLinks(deslinks); removeLinks(tdlinks); removeLinks(iaslinks); removeLinks(mlclinks); removeLinks(llinks); removeLinks(pbplinks); } }); } //To remove extra achor tags of each category (ds, ml, ai) and only have 2 of each category per article cleanLinks(); */ //Recommended Articles var ctaLinks = [ /* ' ' + '

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',*/ ]; var replaceText = { '': '', '': '', '
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