You're starting a career in AI. What are the most important things to know?

My advice for starting a career in AI is to begin by studying its fundamental concepts and principles. Once you have a solid understanding, consider focusing on a specific field within AI that aligns with your interests and career goals. Continuously expand your knowledge base, staying open to learning new developments and exploring interdisciplinary connections. Proficiency in programming, particularly in languages like Python, is essential for AI development, along with strong communication skills, including proficiency in English. Remember, mastering the basics is crucial before delving into more specialized areas, just as learning to walk comes before running in the journey of AI education and career development.

Basics - Most of us think it trivial. It plays a vital role in what one wants to achieve. No authentic, realistic problems can be identified or solved, without basic understanding, Focus on basics through numerous learning, and that would cherish the momentum.

When you start your career in AI I would recommend doing three things: 1) Find a niche in AI that interests you the most 2) Share your knowledge, learning and be as open as possible about your process. 3) Start teaching in your community (however small that community is) When I started in AI field I was sharing my prompts, every tool I found helpful and creative applications of AI. Think outside the box. Write in language that people can understand, unless you're writing for academics. People are still eager to learn and a lot of people have never used AI. By teaching I mean sharing and offering your knowledge to whoever is interested to learn. Start from your family and your close circle, network online.

Think using first principles. Couple science with business context. Think simple. Don't start with a complex solution. With every iteration, increase complexity. Evaluate if introducing complexity brings significantly better outcomes.

AI is broad, but the area to find your niche can come from things that are not about algorithms or technobabble. It can be about having a domain of expertise to come with. For example, if you really know a lot about identifying flowers and then you are applying that to AI, it makes it a lot easier to learn AI because you know what is supposed to be right and it motivates you to train the AI to be better.

With AI evolving rapidly, focusing on a niche not only helps you become an expert but also keeps you ahead in the game. It's about striking the right balance between depth and adaptability. 🎯 Dive into areas that spark your curiosity, whether it's unraveling the complexities of computer vision or exploring the nuances of natural language processing. Remember, being a specialist doesn't mean putting blinders on; it's about deep diving while keeping an eye on the horizon for emerging fields. Let's embrace this exciting journey with an open mind and a keen spirit of exploration! 🚀

During the preparation for our course, AI - BUSINESS, I have considered the T model. This means that the specialisation can have 2 max 3 sub areas, but the top line in the T represent the general skills which can allow the adoption and the implementation of AI Systems.

AI is a vast field with numerous specialties, such as natural language processing, computer vision, or robotics. Explore different areas to find what excites you the most. Specializing allows you to dive deeper into a specific domain, making you more valuable to employers looking for experts in that area.

To choose an AI specialization, you need to: Explore the different aspects and opportunities of AI, such as machine learning, natural language processing, computer vision, robotics, artificial neural networks, expert systems, etc. Find the one that aligns with your interests, skills, and goals. Use online resources and platforms that offer AI education, training, and mentorship, such as [Coursera], [Indeed], [University of San Diego], and [Indeed India].

AI is a vast field with many specialised areas such as machine learning, natural language processing, computer vision, and robotics. Explore different areas of AI to find what interests you the most. Once you have identified your specialisation, focus your learning and skill development in that specific area to become proficient.

𝟯. 𝗖𝗿𝗮𝗳𝘁𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗔𝗜 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 Your portfolio is the showcase of your AI journey, highlighting your skillset and creative thinking. It distinguishes you in the competitive AI landscape. ▪ 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀: Feature solutions to real-world problems or improvements to existing tech. ▪ 𝗢𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻𝘀: Enhance your portfolio and network by engaging with the open-source community.

Creating a portfolio is your golden ticket in the AI world, especially if you're stepping in without a traditional background. Think of it as your personal gallery 🖼️, showcasing your mastery and creativity with AI tools. This is not just about displaying your technical prowess but also about storytelling—how you approached problems, overcame challenges, and achieved results. Embrace platforms like GitHub and Kaggle to share your projects; this not only demonstrates your skills but also your ability to learn and adapt. Remember, a well-crafted portfolio is a powerful conversation starter with potential employers or collaborators. Dive in, experiment, and let your work speak for itself! 🚀

Building a portfolio in AI, in a reinforcement learning. It demonstrates your practical skills and expertise to potential employers or clients. A strong portfolio showcases your ability to conceptualize, implement, and solve real-world problems. It will serve as tangible evidence of your capabilities, especially if you're transitioning into a new role or field. Having a portfolio allows you to showcase your projects. Well-curated portfolio can serve as a conversation starter during job interviews or client meetings. It provides concrete examples for discussing your experiences, technical abilities, and problem-solving approach, ultimately increasing your chances of success in the AI industry.

A well-rounded portfolio showcases your skills, projects, and understanding of AI. It's your visual resume, so invest time in projects that highlight your unique strengths and interests.

Creating a portfolio showcasing your AI projects and accomplishments is essential for demonstrating your skills to potential employers or clients. Document your projects thoroughly, highlighting the problem you solved, the techniques you used, and the results achieved. A well-curated portfolio will serve as evidence of your capabilities and increase your credibility in the AI community.

Embrace lifelong learning as your mantra in the fast-paced world of AI 🚀. The field is always evolving, and staying informed is not just beneficial; it's essential. Dive into forums, podcasts, and webinars. Engage with the community through workshops and online courses. Remember, learning in AI is not a sprint but a marathon 🏃♂️. Your curiosity and willingness to learn continuously are your best tools. Keep challenging yourself and stay adaptable; the journey is as rewarding as the destination! 🌟

The field of AI is changing on a daily basis. Maybe even by the hour. If you stand still for just a minute, the AI world will pass you by. This seems overwhelming though, doesn't it? To address that challenge of the fast-paced world of AI, KEEP LEARNING. Never stop learning. The moment you stop and think "yeah, I know enough", that's when others will pass you by. This doesn't mean sticking your head into books or courses all day and not actually doing things. You can constantly learn a few key ways: * Learn by doing. Try new things. * Learn from experts. Take courses, especially ones that focus on methods vs. specific here today gone tomorrow technologies * Learn from peers. Select a few online or in person events. Squeeze all you can.

Getting started in AI is exciting, but remember that the tech changes FAST. Every week something new is coming and i find it difficult to keep updated about the trends. Become a Hogger: And why not? There are amazing (and often free!) courses, blogs, even Twitter threads that break down complex stuff. Find those you like, make them part of your routine. Projects over Perfection: Don't wait for 'the perfect idea' to start building. Start building and you will learn. Find Your Tribe: AI communities are full of generous people. Seeing what others grapple with, and offering your own help, levels you up surprisingly quickly. You can laos get help.

𝟰. 𝗟𝗶𝗳𝗲𝗹𝗼𝗻𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗶𝗻 𝗔𝗜 AI demands a commitment to continuous education. With the field's swift progress, staying updated is not optional; it’s essential. ▪ 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Use Coursera and others for cutting-edge courses. ▪ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Workshops and conferences are goldmines for learning and networking.

The AI landscape is ever-evolving. Staying updated with the latest research, technologies, and methodologies is key to staying relevant and innovative in the field.

To use AI ethically, begin by obtaining data through transparent means and with explicit consent, ensuring the privacy and rights of individuals are respected. Actively identify and mitigate biases within your AI models to promote fairness, making sure that the technology does not inadvertently discriminate against any group. Strive for transparency by making the decision-making processes of your AI systems understandable to end-users and provide explanations for AI-driven decisions. Implement audits of your AI systems to assess their fairness and accuracy over time. Maintain human oversight to address ethical concerns promptly and to make critical decisions, ensuring that AI serves as a tool for enhancement rather than replacement.

Navigating AI's ethical landscape is akin to walking a tightrope 🎪. As AI practitioners, it's our duty to balance innovation with responsibility. From biases to job displacement and disinformation, the ethical considerations are vast and complex. Ethical AI isn't just about avoiding harm; it's about actively promoting good, respecting user values, and considering the broader societal impact. Let's commit to being the guardians of this technology, ensuring it serves to enhance, not detract from, our collective well-being. Remember: "With great power comes great responsibility!" Let's use AI to pave the way for a more equitable and understanding world. 🌍✨

𝟱. 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗔𝗜 Ethics is not just an add-on; it’s central to AI development. Navigating the moral landscape of AI ensures technology benefits all of humanity. ▪ 𝗟𝗲𝗮𝗿𝗻 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀: Ground yourself in the ethical guidelines shaping responsible AI. ▪ 𝗔𝗱𝘃𝗼𝗰𝗮𝘁𝗲 𝗙𝗮𝗶𝗿𝗻𝗲𝘀𝘀: Commit to developing transparent and equitable AI solutions.

With great power comes great responsibility. Ensure your work in AI adheres to ethical guidelines, respects privacy, and promotes the welfare of all individuals.

In order to be a good AI citizen, I strongly believe that you should spend some time learning around the ethics and sustainability of AI. There are multiple online courses on the topic, including an excellent one by the London School of Economics. There are several Ethics of AI books available that will also give you a base-coat. Going to the core of it all, learning basic ethics and how people's equalities and rights are affected by technology and decisions in general will allow you to better understand how AI can be ethically applied. Start using things like the Microsoft Harms Modelling framework to draw out the potential harms or inequalities of what you're proposing to build.

Enjoy the process of learning, experimenting, and growing. Your passion for AI will be your greatest motivator, driving you to explore, create, and innovate.

𝟲. 𝗘𝗺𝗯𝗿𝗮𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝗔𝗜 𝗔𝗱𝘃𝗲𝗻𝘁𝘂𝗿𝗲 Passion fuels your AI career. Enjoy every step of discovery, creation, and innovation along this exciting journey. ▪ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗮𝘀 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀: Leverage obstacles as catalysts for growth. ▪ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Sharing insights and collaborating enriches your experience and makes AI exploration thrilling.

Enjoying what you do is essential for long-term success and fulfillment in your AI career. Find joy in the process of learning, experimenting, and solving challenging problems. Cultivate a curiosity-driven mindset and embrace the excitement of exploring the possibilities of AI technology.

Our corporate values are Learn, Teach, Grow, Serve, Innovate, and Execute. For us, AI really emphasized those values. Enjoying the journey in AI means embracing the process, celebrating the outcomes, and appreciating the rewards that come from your efforts. It's important to take a moment to pat yourself on the back for your achievements, share what you've learned with others, and inspire those around you to embark on their own AI adventures.

Who says AI can't be fun? 🎉 In the world of AI 👇: - 🧩 Problem-Solving: AI provides a thrilling playground for addressing real-world issues. Checkout Indie Hackers with AI. - 🚀 Innovate: Bring your unique products or services to life with AI. - 🎨 Unleash Your Creativity: AI isn't just for scientists. Artists can express their visions in ways like never before. - 🌱 Explore & Grow: Dive into new domains, learn cutting-edge skills, discover newfound passions. - 💡 Share your Insights: Your achievements are worth celebrating. Share your insights and be the inspiration for others. AI isn't just a field. It's an adventure, teeming with excitement and surprise at every turn. So, buckle up, enjoy the ride, and don't forget to have fun! 🎢

The technology is the "smallest" part of the job. A successful AI leader needs to have a strong grasp of business strategy (and how an organization's vision for AI aligns with it), the human factors and change management, the ability to build relationships, communicate, and influence across organizational silos, and more. While yes, of course there's a need for skilled AI researchers, developers, etc., the field *really* needs well-rounded business people who understand that AI is a means to and end, with productivity, performance, innovation, and so on being the ends...

There is one thing that anyone who wants starting a career should consider. It doesn't hurt... Self Analyse your biases firstly 1 rely too much on societal and professional stereotypes 2. Overvalue their personal experiences, especially recent ones 3. Overvalue their personal gut feel 4. confirmation bias 5. Resist admitting mistakes 6. Struggle to keep up with the skills and literature in their fields 7 Avoid criticizing, evaluating, or disciplining their peers and their.dame work 8 over rely on AI... You can check if there is any risk.now and in the future that these biases come out.

Recently, people have used ChatGPT and other generative AI tools to accomplish wonderful things and to produce very creative outputs using effective text prompts. That is an intended consequence of "democratizing AI", to make AI accessible and available to a broader audience. While "prompt engineering" is important for effectively using generative AI tools, knowledge of prompt engineering by itself doesn't equate to being an "AI specialist". A prompt engineer is more of a language specialist who knows how to craft the appropriate sentences (the prompt) to generate the desired output from the generative AI. An AI specialist should know prompt engineering, but also a much deeper understanding of machine learning and other AI frameworks.

Networking with peers, seeking mentorship, and engaging with the AI community can provide invaluable insights, opportunities for collaboration, and feedback on your work.

I think for AI relevant small internships can be super useful. Internships in any startups would help you apply theoretical knowledge in real-world scenarios, and develop problem-solving skills. This would be a great way to boost your confidence in your new acquired abilities and learnings.