You're considering a career in AI. How can you make sure you're ready for the challenges ahead?

Die KI umfasst verschiedene Bereiche. Ein gutes Verst?ndnis der Grundlagen macht es m?glich, die Vielfalt der Probleme zu erfassen. Ohne diese Basis besteht die Gefahr, dass man sich in der Fülle von Begriffen und Technologien verliert. Die unterschiedlichen Vorstellungen, die der Begriff Künstliche Intelligenz hervorruft, machen deutlich, wie wichtig es ist, nicht nur ein Grundverst?ndnis zu erlangen, sondern auch die Vielfalt der relevanten KI-Bereiche zu erkunden. Das Erlernen der Grundlagen muss nicht mühsam sein. Mit den richtigen Ressourcen wie etwa Online-Kursen ist es nicht so schwierig, sich die Grundlagen anzueignen. Echtes Interesse und die Neugierde, Projekte selbst auszuprobieren, machen den Lernprozess spannend und greifbar.

Begin by acquiring a strong understanding of AI basics, including its history, concepts, applications, and limitations. Establish a robust foundation in mathematics, statistics, and programming, as these are indispensable tools in AI. Utilize online courses, books, and tutorials to grasp the fundamentals and delve into specific subfields. Continuous learning and practical application of knowledge will ensure you're well-equipped to tackle the challenges in the dynamic field of AI.

Prepare for a career in AI by building a strong foundation in mathematics, statistics, and programming. Acquire expertise in machine learning algorithms and frameworks. Engage in real-world projects to apply theoretical knowledge. Stay updated on the latest research through conferences, journals, and online courses. Cultivate problem-solving skills and a deep understanding of business domains. Collaborate with peers, participate in hackathons, and contribute to open-source projects. Develop a diverse skill set, including natural language processing and computer vision. Stay adaptable as AI evolves, embrace challenges, and continuously enhance your skills to thrive in this dynamic field.

One thing I have found helpful in preparing for a career in AI is to continually learn and stay updated with the latest developments in the field. This includes taking online courses, attending workshops, and participating in AI-related forums and discussions. For example, I've seen aspiring AI professionals benefit greatly from completing specialized courses in machine learning and data science, and actively participating in AI projects or hackathons. This continuous learning approach ensures that you not only gain the necessary technical skills but also remain adaptable and informed about evolving AI trends and technologies.

Learn the basics of AI through online courses and tutorials. You may start with the free resources available and consider subscribing to paid training resources and workshops. At some point, you could spend more time reading books and even research papers which would help you solidify your knowledge on AI along with its subfields.

My view, if you are planning for career transition, study Basic concepts like Statistics,Machine Learning participate in Hacker Rank make sure good in Basics that enough, Next step, work projects not only Kaggle datasets, work on live projects for getting experiences. No Need to everything, First step, enter into this domain with this basics, then improve. Overall,Continuous learning will help.

Yes, new developments are coming in the AI field every day but if your fundamentals are strong and basic understanding of how AI-based product development happens, then you are in the game. No need to learn everything, learn as you need.

Progress to the practical application of AI principles by engaging in hands-on projects and advanced learning to hone your technical skills.

Understanding the capabilities of AI/ML platforms, frameworks, and services (as well as what problems and challenges these features solve) would help you prepare for more advanced and specific use cases which may come up when working on future AI requirements and projects. Doing this research ahead of time would help you develop your skills and make more informed decisions especially when choosing and using the right tools for the job.

The best way to develop your AI skills is to always apply and test what you have learnt. Share your knowledge here on LinkedIn, for example. As you summarise your learnings, you will notice that what you have learned is deepened. And you go from being a learner to a teacher. Others in your network will notice your growth and see that you are building up expertise. There are also learning circles on the topic such as #WOL-Circle or #lernOS-Circle where you can learn together with others. At Lernos, some AI professionals are already in the process of developing a lernos guide "AI for beginners".

?? ???????????????????? ???? ???????????? ?????????????????????? ???????????? ?? ???????? ????????????????? ?? Here are few things that you can do- 1. ?? Efficient Learning- Opt for short, focused online AI courses or podcasts during commutes, Listen to AI webinars or talks while multitasking 2. ?? Networking on the Go - Engage in AI-related LinkedIn groups during breaks 3. ?? Practical Application- Implement small AI elements in current work projects if applicable. Set aside a dedicated, albeit brief, weekly time for personal AI projects 4. ???? Seek Virtual Mentorship Connect with AI mentors through online platforms for flexible interactions 5. ?? Adapt and Integrate-Prioritize AI trends or skills most relevant to your field or interest.

After acquiring a solid foundation in fundamental AI concepts, you can stay updated by immersing yourself in the ever-evolving AI landscape through continuous learning. Regularly read reputable journals, research publications, and industry blogs to stay informed about emerging trends and breakthroughs. Actively participate in AI communities, attend conferences, and join relevant forums to connect with professionals and gain insights from their experiences.

This may be an unpopular opinion but the way you stay updated is not by the news or online courses. It's by building your portfolio of small projects. Here's why: 1. AI Hype - Technology media is known to sensationalise technology. When building projects, you quickly learn what technology can and can't do. 2. Impactful conversations - Some of the best conversations come from debugging a project or discussing creative ideas. This increases your knowledge of what's possible. 3. Technology Trajectory - As a builder you are more capable to understand what's possible and the direction the technology and industry is heading in overtime because you've worked with the progression with your own hands.

It's good to keep balance between exploration and exploitation while tracking AI as a field. Given the current pace of development, we can expect thousands of new AI algorithms and paradigms in the coming years... but only a few will revolutionize the field. Furthermore, the governments, the click-baity press and online influencers will create lots of fear and confusion. Therefore, apply a mental diet when it comes to tracking the field of AI: follow a curated list of experts online and trusted press outlets.

The pace of innovative technology leveraging AI is quite fast and it may look difficult for you to jump in halfway. However, one must also realize that what's new today, is the culmination of months of years of work that has been put forth until now. And the basic tools and requirements for this result to be achieved have always been there for anyone to utilize. What sets them apart is the fact that they chose to pursue a new direction with the tools in hand. This is why I would encourage more people to keep updating themselves with what's happening every day. It will help you discover new paradigms and technologies that may help you advance your own projects to a different level.

Approaching AI with ethics in mind is so critical, & yet so often overlooked (or outright discouraged, though not in so many words). Much of the contemporary large/foundation model paradigm is the product of skating on the questionable side of legal/ethical gray areas (what data was used to train models, how it was gathered, how it was cleaned, etc). We’re witnessing the fallout of this approach in the form of lawsuits, but for folks or teams coming to this topic fresh, this is a chance to develop a set of principles from which to operate, state them clearly for stakeholders (if possible even make them accessible to the public), & stand by them—even when it might cost more to do so. Otherwise perverse incentives will perpetuate status quo.

We all have to approach AI ethically and responsibly. We must ensure that AI is used in a way that respects human rights and ethical values. We must make sure that the data that is used to train smart models accurately reflects reality and does not contain any biases. These models must be designed in a way that ensures fairness, transparency, and accountability. When developing AI, this must be done in a way that respects the privacy, security, personal freedom, and moral and cultural values of the communities in which it is used. AI must be developed in a way that respects the environment, conserves natural resources, and respects local and international laws and regulations.

From my experience, especially in the realm of AI and web application development, being ethical is paramount. AI isn’t just about technology; it’s deeply intertwined with societal and ethical considerations. It’s essential to contemplate the impact of AI on society, humanity, and the environment. Ethical considerations must be at the forefront during the design, development, and deployment of AI systems. This means respecting the values, rights, and needs of all stakeholders and users. Adhering to responsible and trustworthy AI principles is non-negotiable. Be ethical in handling data, using algorithms, and developing models. Also, maintain ethical standards in communication, collaboration, and education in AI.

As of today, in vast majority of situations, we are not required to disclose whether and to what extent we use AI for work. However, trust is the currency of the future. Legislation tends to follow technological progress with a massive delay - but it will catch up one day. Therefore, take good care of your reputation now and disclose any interactions with AI that you might undertake at work to your superior (if you are an employee), your followers (if you are an online creator), or your clients (if you are an entrepreneur).

Beyond technical prowess, recognize the societal and environmental impacts. Uphold ethics in every stage – from design to deployment. Prioritize stakeholders' values, rights, and needs. Adhere to principles of responsible and trustworthy AI. Ethically handle data, algorithms, and models. Communicate, collaborate, and educate with integrity. Strive to ensure AI's positive impact on society, humanity, and the world.

If you are considering in a career in AI, your work-life balance should be of high priority. The whole point of AI assisting us in the first place is to enable us humans focus on the things that really matter and mean something to us. So, it is important you commit to family, community and great life experiences just as much as you develop your AI skills and build useful models.

According to me, first make your health, then make your wealth. A good healthy mind can grasp more in the same amount of time as compared to a non healthy person. Take a full day rest after an exam or project deadline which will help your body to recover.

Maintaining a healthy work-life balance is essential in the dynamic field of AI. Amidst its demands, prioritize your physical, mental, and emotional well-being. Cultivate interests and passions beyond AI, fostering a balanced life. Surround yourself with a supportive network of friends and family, finding motivation and enrichment. Seek purpose and fulfillment both in your AI career and life's broader journey. Striking this balance ensures sustained success and well-being.

Honestly, I've not learnt to deal with this correctly yet but my higher ups always told me not to do a lot and end up having a burn out . So beware!

There is hardly a future career today that does not involve #AI. So whatever you do, you probably need to prepare- understand how it can enhance or even replace what you do. You cannot prevent the change- rather, embrace it, be a part of it, and lead it.

AI careers involve grappling with rapid technological shifts, data biases, and complex algorithms. Access to computational resources and the need for interdisciplinary skills add complexity. Balancing ethics, evolving regulations, and a competitive job market amplify the challenges. Success requires adaptability, continual learning, diverse skills, ethical practice, and staying updated with trends and regulations to navigate these multifaceted challenges effectively.

The field of AI isn't limited to programming and technical roles. There are numerous careers involving AI that we might not yet fully envision. Even if you're not an engineer or IT expert, you can still have a career in AI. Consider the future of your job and how AI can enhance it, whether you're e.g. in marketing, law, insurance, or a hands-on trade. As an AI specialist in your industry or area of expertise, you may be among the pioneers, enjoying the benefits of being at the forefront of this evolving domain.

Adopt emerging technologies, attend conferences, & experiment with new frameworks. I once used outdated methods, missing out on groundbreaking innovations. By cultivating curiosity & venturing into uncharted territories, I discovered powerful techniques, built a culture of experimentation in my team, & witnessed us navigate towards cutting-edge solutions. Stay current with research papers, participate in online communities, & actively seek out challenges that stretch your abilities. By embracing continuous learning & pushing my boundaries, I kept pace with the rapid evolution of AI & unlocked hidden potential within myself.

Embarking on the incredible journey of AI in 2023, where technological frontiers are constantly expanding. From the seamless fusion of Edge AI with real-time applications to the transformative synergy between edge computing and artificial intelligence, we're scripting a remarkable narrative of innovation. Embracing this era at the intersection of technology and intelligence is nothing short of amazing. Join me in exploring the boundless possibilities!