Here's how you can acquire the most sought-after AI skills by employers.

Having an in-depth knowledge of AI basics and how they can help enhance your work before digging into the advanced level of development the better help you be fully grounded in AI practices and guidelines.

To acquire the most sought-after AI skills by employers, focus on in-demand areas like machine learning, deep learning, and natural language processing. Utilize online platforms and courses for learning, engage in hands-on projects, and stay updated on industry trends. Collaborate with peers, seek mentorship, and continuously improve to position yourself as a valuable AI professional.

Premier point : Rassurez-vous, la plupart des employeurs ne ma?trisent pas en détails ce qu'est l'IA... Donc à moins de vouloir travailler directement dans le développement software lié à l'IA, vous aurez tout le temps d'acquérir progressivement les bases de l'IA, en commen?ant pour la compréhension de "comment ?a marche"... Intéressez-vous au fonctionnement d'un réseau neuronal, de comment fonctionne un RAG... et surtout lisez, il y a trois tonnes de choses intéressantes à découvrir dans les livre de Yann LeCun, Daniel Kahneman, Luc Julia, Aurélie Jean... Ensuite, n'hésitez pas à vous monter une petite sandbox pour essayer les choses, ce ne sont pas les infos qui manquent sur le web... Commencez par ex à créer un GPT, pas besoin de code !

To acquire the most sought-after AI skills by employers, start by learning the basics through online courses, tutorials, and books. Apply knowledge by building projects that demonstrate proficiency in areas like machine learning, deep learning, and natural language processing. Engage in advanced learning through specialized courses, workshops, and research opportunities to deepen understanding and expertise. Network widely within the AI community through conferences, meetups, and online forums to exchange ideas, collaborate on projects, and explore job opportunities. Cultivate critical thinking skills to solve complex problems and innovate in AI applications.

Roll up your sleeves and dive into real-world projects. Sure, learning the fundamentals is crucial, but there's nothing quite like the thrill of applying that knowledge to build something tangible.

Building projects is crucial for solidifying skills and showcasing them to potential employers. However, it's vital to choose projects that challenge you and allow you to apply advanced AI concepts. Moreover, detailed documentation not only showcases your technical skills but also your ability to communicate and structure projects, which is valuable in any AI role.

Apply your knowledge by creating projects. Hands-on experience reinforces learning and showcases skills to employers. Begin with simple projects like a chatbot or recommendation system, then tackle more complex challenges. Documenting projects in a portfolio demonstrates problem-solving abilities and ability to turn theoretical knowledge into practical solutions.

Sugiro que comece a construir projetos práticos de IA assim que tiver uma base teórica sólida. Por exemplo, inicie com projetos simples como desenvolver um chatbot e gradualmente avance para sistemas mais complexos, como algoritmos de previs?o. A chave aqui é a documenta??o detalhada de cada projeto em seu portfólio, o que demonstra aos empregadores n?o apenas sua capacidade técnica, mas também seu processo de pensamento e habilidade em aplicar teoria à prática. Isso é crucial para se destacar no mercado de trabalho de IA.

When it comes to acquiring in-demand AI skills, hands-on experience through project building is the best way to go. You can start by identifying a project that aligns with your interests and the skills that you want to develop. Start with simple projects and then gradually take on more complex challenges. By working on AI projects, you will not only gain practical experience but also demonstrate your proficiency and readiness to solve real-world problems/challenges in the AI world. This will certainly make you a desirable candidate.

Once proficient in basics and with practical experience, delve into advanced AI topics like deep learning, reinforcement learning, and computer vision. Specialized courses provide insights into algorithms and real-world applications. Stay updated with the latest advancements in the constantly evolving field of AI.

Vertiefe deine Kenntnisse durch fortgeschrittene Kurse und Spezialisierungen in Bereichen wie Deep Learning, Computer Vision oder Natural Language Processing.

Busque cursos especializados nessas tecnologias para entender a fundo os algoritmos e suas aplica??es práticas. Manter-se atualizado é essencial, pois o campo da IA evolui rapidamente. Investir em aprendizado contínuo n?o só amplia suas habilidades, mas também posiciona você como um profissional valioso no mercado de trabalho.

Advanced learning is crucial to excel in AI, but don't limit yourself to formal courses. Dive into papers, engage with communities, and undertake hands-on projects in these areas. This mix will provide you with a deeper understanding and practical skills to tackle real-world challenges in the field.

After mastering the basics and gaining some practical experience, it's time to explore advanced AI topics. Areas like deep learning, reinforcement learning, and computer vision are highly sought after. Look for specialized courses to help you grasp the complexities of these algorithms and their real-world applications. Keep in mind that AI is always evolving, so it's important to stay updated with the latest advancements to remain competitive in the field.

Nous avons la chance de vivre dans un monde qui croule sous l'information... Profitez de cette richesse pour trouver un maximum de sources auprès des bonnes personnes... Réseautez sur LinkedIn ou Twitter, qui seront les 2 principales sources pour trouver les personnes intéressantes, mais ne vous contentez pas de vous connecter mollement à elles, n'hésitez pas à interagir, poser des questions... Vous verrez que certain(e)s ne sont pas si inatteignables que ?a... Rejoignez aussi les communautés, surtout si vous savez déjà coder : GitHub / BitBucket / GitLab sont de formidables sources d'infos et d'échanges...

Vernetze dich breit und tief mit anderen KI-Profis, sei es online oder bei Konferenzen. Dies kann dir nicht nur neue Perspektiven er?ffnen, sondern auch Karrierechancen bieten.

Networking is crucial in AI as in any career. Attend AI conferences, seminars, and meetups to connect with industry professionals. Engage in online forums and social media groups dedicated to AI for insights into industry needs and trends, and potential job opportunities. Being part of a community offers invaluable support as you navigate the complexities of AI.

Building a strong network is vital in AI, but quality trumps quantity. Focus on forging meaningful relationships with industry experts and mentors. These connections will not only provide you with valuable insights but also opportunities for collaboration and mutual learning.

Networking is crucial in any career, including AI. Attend AI conferences, seminars, and meetups to connect with professionals in the field. Join online forums and social media groups focused on AI. These connections can offer insights into industry needs, emerging trends, and potential job opportunities. Plus, being part of a community provides support as you navigate the complexities of AI, helping you stay motivated and informed.

n AI, technical expertise must be complemented by critical thinking skills. Employers seek candidates who can navigate AI challenges with a nuanced perspective. This includes understanding societal impacts, ensuring fairness and transparency in algorithms, and addressing privacy concerns. Cultivate these soft skills to become a well-rounded AI professional.

Critical thinking is crucial in AI, beyond just coding and algorithms. You need to be prepared to question and assess the ethical and social implications of your projects. This not only makes you more employable but also contributes to developing more responsible and ethical solutions.

In the world of AI, it's not just about technical skills; it's also about using these tools ethically and effectively. Employers look for candidates who can think critically and tackle AI challenges with a balanced perspective. This means considering the societal impacts of AI, making sure algorithms are fair and transparent, and respecting people's privacy. Develop these soft skills to become a more well-rounded AI professional, valued for your ability to navigate the complex ethical landscape of technology.

In my view, acquiring the most sought-after AI skills isn't just about mastering complex algorithms or crunching massive datasets. While technical expertise is undoubtedly crucial, the real game-changer lies in your ability to think creatively and approach problems from unconventional angles.

Bleib immer auf dem Laufenden über die neuesten Entwicklungen und Trends im Bereich der KI. Die Technologie entwickelt sich rasch weiter, und fortlaufendes Lernen ist entscheidend.

In the world of AI, things are always changing, and it's important to keep up. Stay in the loop by following top AI researchers, subscribing to relevant journals, and joining online communities where you can discuss the latest developments. Continuous learning not only keeps your passion for AI alive but also ensures that your skills stay in demand by employers who want to stay ahead of the curve. It's like staying tuned in to your favorite show—you never want to miss an episode!

To learn AI skills in demand: - Identify AI knowledge and skills sought, by reading the job descriptions of AI jobs that you eventually want. - Take relevant AI courses in university and / or online. - Build your own AI projects, and present them on your personal website, GitHub, LinkedIn, etc. - Regularly read AI news (e.g., go to news.google.com -> Technology -> AI) and AI research papers (search for AI journals, and AI topics on scholar.google.com). - Conduct AI research (if possible, under guidance of a professor or researcher) and try to publish research papers in journals and conferences. - Network and discuss with other professionals in AI (e.g., classmates, co-workers, alumni, researchers, industry, etc.).

Start developing your own projects as soon as possible. This is the most effective and fast way to learn how AI works and how to develop AI projects. During the development you will encounter lots of errors which you will need to solve to continue. While solving those problems you will find other AI applications and you will enforce your AI knowledge.