Artificial Intelligence is reshaping every industry today. According to research by McKinsey, AI could create an economic value of over $13 trillion globally by 2030. People have already started learning new and in-demand AI skills to have an early mover’s advantage.
This exponential growth is also exponentially increasing the demand for AI talents with specialized skills. We will now explore the skills that can set you apart and position you for long, rewarding AI careers. You’ll also find actionable insights into how you can smartly learn these abilities.
By enhancing your technical knowledge and aptitude with the right efforts, coveted high-paying AI jobs in machine learning, deep learning, and neural linking can be easily within your reach.
What Are AI Skills?
In-demand AI skills encompass proficiency across various branches of artificial intelligence, including machine learning, deep learning, and cutting-edge abilities in generative models.
Skills also span understanding data, analytics, mathematics, statistics, and programming to actually build and deploy projects. Additionally, expertise in domains like computer vision, NLP, neural networks, and recommendation systems makes talents more specialized and sought-after.
With AI transforming businesses and lives, dedicated efforts to master cash-paying jobs like MLOps, prompt engineering, and AI application development will be highly rewarded with higher employability and compensation. You can truly future-proof your career by gaining multi-faceted AI superpowers.
Top 15 In-Demand AI Skills To Learn This Year
Artificial intelligence is rising around the globe, and 2024 is the right time to adopt this new technology in every field. If you aim for a high-paying job, AI skills are a must. Here are the 15 most in-demand AI skills you must learn this year.
1. Generative AI And Large Language Models (LLMs)
Generative AI that can produce human-like content, images, code, and more is in huge demand. Skills in LLMs like Claude and OpenAI’s GPT-4 are vital to land AI jobs, as these are the most high-demand AI skills.
The global AI market may reach $500 billion by the end of 2024, reports PwC. As per McKinsey, generative AI could create $3.5 trillion to $5.8 trillion in value annually by 2030.
Salaries for ML engineers and researchers are over $150k, reports Indeed. Freelancers charge $30 to $75 per hour. However, creating demos helps to showcase skills. Building a portfolio is also a key to demonstrating abilities to employers.
With practice, anyone can gain skills in 6 months. Learn via YouTube tutorials from Anthropic, Google Developers, PyTorch, and more. Take free courses on Coursera or Udacity. Join Kaggle competitions. Contribute to open-sourced generative AI projects on GitHub.
2. Prompt Engineering
Prompt engineering is a must-have skill for AI jobs. You can get both full-time and part-time weekend jobs with this skill. With LLMs understanding prompts better than humans, optimizing prompts unlocks their potential.
As per Accenture, 87% of executives will adopt LLMs over the next two years. Prompt engineering roles can pay over $150k, reports Indeed. Or you can charge $40-100 per hour as a freelancer. Prompt skills take only 3-6 months to develop with practice.
Study the principles from Anthropic’s open-sourced Claude prompts. Analyze prompts from leaders like OpenAI and Google. Tweak prompts and note differences. You can also take the free 12-week Coursera course to learn it.
We also recommend Anthropic and OpenAI docs. Plus, lectures from MIT scholars on prompt anatomy. You can also sign up for Kaggle’s prompt challenges to test skills. With dedicated practice, you’ll ace prompt engineering in no time.
3. AI Model Tuning
Tuning AI models like Claude or GPT-4 for optimal performance is crucial. It is also among the most in-demand AI skills to learn. With personalized models and “tuning as a service” gaining steam, this skill will be highly valued.
Salaries exceed $150,000 for full-time roles per Glassdoor. Freelance tuning experts earn $50-125/hour. With hands-on practice, one can develop strong tuning skills in 4-8 months.
First, learn tuning fundamentals from the University of Helsinki’s free course. Then, study Anthropic’s open-sourced tuning techniques. Additionally, leverage Google’s ML crash course for real-world projects to practice.
Join Kaggle competitions like NLP Fine-Tuning to test abilities. Contribute to open-source model tuning projects on GitHub. Creating a portfolio of tuned models helps showcase your expertise to potential employers or clients.
4. Programming Languages
Programming is one of the best AI skills to learn that lets you build, test, and deploy AI systems. Python and SQL are most in demand. But C++, Java, R, and JavaScript are gaining traction too. If you are looking for remote jobs for college students, you can also learn these languages.
As per Tractica, enterprise AI software revenue will reach $52 billion by 2027. So, coders will stay high value. Full-time programming salaries exceed $100k, according to PayScale. Freelancers charge $30-150 per hour. You can gain job-ready coding skills in 6-12 months!
First, master Python via Udemy’s free course. Then, learn AI application development through EdX programs. Hone data science coding abilities with Google’s Python certificate. Solve real-world problems on Kaggle.
Contribute to open-source ML projects on GitHub using trending languages like Python, SQL, C++, and JavaScript. Building 3-5 apps helps create a portfolio to showcase skills. Our developer community provides mentorship and expert code reviews, too.
5. Natural Language Processing (NLP)
NLP powers chatbots, search engines, autocorrect, and more. As per Gartner, NLP’s business value will touch $36+ billion by 2026. So, specialized NLP skills mean higher employability and pay.
NLP engineers earn over $120k, reports Glassdoor. Freelancers charge $30-100/hour. With practice, you can develop industry-ready NLP abilities in 4-8 months.
Start with free NLP basics courses from Stanford University and deep learning AI. Then, take NLP specializations via Coursera. Learn to apply NLP for real-world problems with hands-on Kaggle competitions. Furthermore, study Anthropic’s open-sourced NLP codebase on GitHub.
Contribute to open-source NLP projects. Create NLP demos for your portfolio using tools like HuggingFace and TensorFlow. Join developer communities like Gitter for troubleshooting help. In 6 months, you can have professional-grade NLP abilities to set you apart.
6. Machine Learning
Machine Learning is transforming every industry today. Skills to build, deploy, and maintain ML systems are vital for future-proof careers.
ML engineer salaries can exceed $150k, says Indeed. Freelance ML experts charge over $100 per hour. The news gets better. With dedication, you can gain professional ML skills within 6-12 months!
Start by learning Python machine learning basics through IBM’s free course. Get an overview of popular ML algorithms via Tutorialspoint. Hone practical skills with hands-on projects from Coursera’s Google ML certificate.
Participate in Kaggle competitions to test your abilities. Moreover, study Anthropic’s ML codebase and contribute to open-source ML projects on GitHub. Create 3-5 ML model demos for your portfolio with tools like Scikit-Learn.
For troubleshooting, leverage developer communities like Stack Overflow. Working hard pays off, as you’ll soon stand out with in-demand ML skills!
7. Deep Learning
Deep learning drives breakthroughs in speech recognition, computer vision, chatbots, and more. So, specialized deep-learning skills will be highly valued.
Deep learning engineer salaries exceed $150k on Glassdoor. Freelancers can command over $125/hour. You can gain professional-grade skills in 6-12 months with determination!
Start by learning deep learning fundamentals via MIT’s intro course for free. Then, take Andrew Ng’s acclaimed DeepLearning AI specialization on Coursera. Hone skills by working on computer vision and NLP projects on Kaggle. Furthermore, study Anthropic’s Claude and contribute to deep learning projects on GitHub using libraries like TensorFlow and PyTorch.
Create 3-5 demos for your portfolio. Join developer Slack channels for troubleshooting help. With consistent practice, you will gain specialized abilities to advance your AI career in no time!
8. Image processing / Computer Vision
Computer vision has applications in autonomous vehicles, security, manufacturing, and more. According to Tractica, computer vision is one of the highest-paying and in-demand AI skills. So, specialized skills in computer vision algorithms, model building, and deployment will be prized talents.
Full-time salaries exceed $150k per Glassdoor. Consultants can make over $100 per hour. With diligent efforts, you can develop professional-grade skills in about 6 months!
Start with fundamentals through Udacity’s popular free course. Then, get extensive hands-on training via Coursera’s computer vision specialization by IBM. Hone abilities by participating in Kaggle competitions like Carvana.
Additionally, contribute to projects on GitHub using libraries like OpenCV. Build a diverse portfolio of 3-5 demos to showcase skills. Join communities like Slack and Stack Overflow for troubleshooting help. Stay motivated and persistent, and you’ll soon stand out with specialized computer vision abilities!
9. Data Modelling
With data growing exponentially, skills to structure, access, and analyze data are essential. It is not just one of the high-demand AI skills but also among the high-income skills to learn this year.
Data modeling helps derive value via SQL, NoSQL, graph databases, and more. According to IBM, demand for data modeling talent exceeds supply by over 23%.
So strong abilities can ensure high pay, with salaries over $120k, says Glassdoor. Freelance data modelers charge $60-150 per hour as well. Now for the sweet part – one can gain industry-ready skills in 4-8 months through rigorous efforts!
Start by grasping fundamentals from Google’s crash course and then do an extensive course on Coursera to gain SQL and NoSQL modeling practice. Study open-sourced examples of data models on GitHub.
Additionally, you should create at least 3 sample projects using MongoDB, Redis, and Neo4j for hands-on learning. Showcase your work via Tableau dashboards. Developer forums like Stack Overflow can help with debugging.
10. Data Analytics
Data analytics helps uncover trends and derive business value from data. As companies become data-driven, analytics talents who can gather, analyze, and translate data into insights using SQL, Python, R, and tools like Power BI are highly sought-after.
Average salaries can exceed $95k, reports Glassdoor. Some freelancers make up to $175 per hour. The sweet deal, though? One can gain job-ready data analytics abilities within 6 months by being focused!
Start with IBM’s comprehensive and free course covering data visualization, statistical analysis, and more. Next, do extensive hands-on projects via Google’s professional certificate on Coursera. Further, build skills by solving real-world problems on Kaggle using popular analytics tools.
Create visualizations and dashboards to form a portfolio. Join active Slack communities to collaborate and get help. By dedicating 6 months to learning in-demand analytics skills, you can shape a lucrative data-driven career!
11. Neural Network
Neural networks power computer vision, NLP, recommendation systems, and more. It is also among the most in-demand AI skills to learn in 2024. As per market reports, enterprise AI software spending will reach $36 billion by 2025.
One can earn over $150k as a full-time engineer per Glassdoor. Freelance NN developers charge around $125 per hour. Now, let’s get you skills-ready! With strong efforts, you can gain professional abilities in 6 to 8 months.
Start with Andrew Ng’s deep learning AI course for neural network fundamentals. Next, get extensive hands-on practice via Coursera’s advanced NN program. Hone skills by working on projects using TensorFlow and Keras. Study and contribute to open-sourced networks on GitHub.
Build a portfolio of 3-5 demos showcasing your work. Developer forums like PyTorch Discussions can help with debugging. Stay persistent through the learning period, and your neural network skills will make you highly employable!
12. AI Libraries And Frameworks
Skills in top AI libraries like NumPy, Pandas, TensorFlow, and PyTorch and frameworks like Keras allow you to build, test and deploy projects. So, mastering these AI skills to learn this year ensures higher employability and pay.
Full-time salaries can exceed $130k per PayScale. Freelancers charge around $75 per hour. Now for the deal – you can gain a working knowledge of key libraries in 4-6 dedicated months!
Start by learning NumPy for data analysis via Udemy’s free course. Then, grasp ML fundamentals with TensorFlow’s crash course. Get extensive hands-on practice with core libraries by doing projects from Coursera’s AI Engineer certificate.
Contribute to open-source projects on GitHub using popular frameworks. Create at least 5 portfolio demos showcasing abilities. Connect with developer communities when facing roadblocks. Stay determined through the learning period, and specialized library skills will accelerate your AI career!
13. Cloud Computing
Cloud infrastructure powers AI innovations and applications today. Skills in working with popular platforms like AWS, GCP, and Azure ensure high employability. As per IDC, over 90% of enterprises use cloud for AI. So, cloud-based abilities are vital for future-ready AI careers.
One can make over $120k as a cloud engineer, says Glassdoor. Freelancers charge around $75 per hour. With rigorous efforts, professional cloud skills can be built within 6 months!
Start by learning fundamentals through Google Cloud’s training course. Then, get extensive hands-on experience via Coursera’s IBM certificate for cloud architecture. Work on real-world projects and case studies and contribute to cloud-based projects on GitHub.
Create 2-3 demo applications showcasing abilities. Developer forums like Hashnode can help troubleshoot issues. So, stay focused through the learning phase, and your cloud skills will propel your AI career ahead!
14. Mathematics
A strong grasp of mathematics, especially linear algebra, calculus, probability, and permutations, is key to excelling in AI. The algorithms, logic, and techniques underpinning breakthroughs in machine learning, computer vision, and NLP involve complex math.
Skills to build models, analyze performance, and improve accuracy require mathematical competence.
Start by brushing up on the basics at Khan Academy. Take advanced courses on matrices and multivariate calculus via edX programs. Learn probability theory and Bayesian stats through lectures from renowned MIT math professors. Solve problems on Project Euler to apply skills.
Join communities like Mathematica Stack Exchange to clear doubts. Consistently practicing challenging math questions is what will sharpen your abilities to apply mathematical concepts for AI.
15. Statistics
You may not believe it, but statistics is one of the most-used AI skills to learn. Expertise in statistics allows for the processing of messy real-world data for AI models. Skills in descriptive statistics, hypothesis testing, regression models, and predictive analysis are imperative.
Statistical prowess lets you evaluate model performance, improve accuracy metrics, and derive insights from data patterns.
Start by revising the basics of descriptive stats via MIT courseware. Learn predictive modeling and data mining techniques through University of Michigan’s courses on Coursera. Master statistical analysis for data science using Python libraries with Udacity programs.
Practice skills by analyzing datasets on Kaggle to unearth insights. Join stats communities like Cross Validated forums to collaborate. The foundation of any robust AI system is statistically sound data analysis and investing time in mastering the prerequisite stats skills.
Top 5 In-Demand AI Soft Skills to Learn In 2024
In-demand AI Skills require more than just technical abilities. Even same-day pay jobs like freelancing demand certain soft skills, too. This includes skills in communication and leadership, the ability to direct complex projects, creative problem-solving, and a growth mindset.
1. Creativity
Creativity enables exploring problems from new perspectives and designing innovative solutions. As AI evolves rapidly, a creative bend aids prompt engineering for models, conducting insightful analysis, and communicating ideas inventively.
Start exercising creative muscles via Cerego’s acclaimed training programs. Then, practice lateral thinking techniques through free courses on how to think out of the box. Additionally, you should learn creative frameworks like design thinking with MIT lectures to apply imagination.
Brainstorm ideas without judging initially and build on others’ concepts, too. This strengthens creative confidence over time. Remember, some of the most impactful AI advances have germinated from creativity.
2. Problem-Solving
AI roles demand analyzing complex problems and designing optimal solutions. Strong problem-solving skills enable tackling challenges in data analysis, model building, accuracy improvements, and more.
Start honing skills via Coursera’s critical thinking course that walks through frameworks. Then, practice problem comprehension and root cause analysis with McKinsey’s business simulations. Learn lateral thinking approaches to avoid initial bias or assumptions.
Work on Project Euler math problems to test skills. Discussing cases in online communities gives exposure, too. Remember, meticulous problem-solving coupled with creativity seeds AI magic!
3. Critical Thinking
In-demand AI skills require strong critical thinking abilities to question assumptions, analyze data patterns thoroughly, evaluate model performance metrics, and more.
Low-stress jobs like freelancing also demand impartiality in decision-making. Start developing skills via the University of California’s acclaimed critical thinking course on Coursera. Then, solve problems and riddles on Brilliant to build logic and rationality.
Additionally, participate in dataset challenges and document limitations or potential biases seen in data. Getting diverse perspectives allows for making informed choices. Remember, asking the right critical questions is what unlocks innovation in AI.
4. Team Game
AI innovation is accelerated through effective collaboration. Skills to lead brainstorming aligned to shared goals, resolve conflicts, and provide constructive feedback are key to successful outcomes.
Start cultivating strong teamwork abilities via Coursera’s project management course covering frameworks to enable synergy. Analyze great leaders to learn motivational tactics. Lead small-group assignments during learning programs for the experience.
Active listening, empathy, and influencing others politely foster creativity. Remember, AI advances fastest when strong team players come together in pursuit of solving meaningful problems that make lives better!
5. AI Ethics
As AI systems grow more powerful, ethical diligence ensures they remain safe and beneficial for all. It is also among the most in-demand AI skills to learn in 2024. Skills in recognizing bias, auditing data, questionnaires, and models proactively, and documenting limitations transparently are vital.
You can start by learning ethical frameworks and privacy guidelines via Harvard University’s online program. Then, keep updated on policies from authorities like the EU Ethics Guidelines for Trustworthy AI.
Additionally, contribute to initiatives like Anthropic’s ethics counseling and OpenAI’s public benefit pledges. Promoting diversity and positive social change must supersede commercial interests. Upholding ethical AI practices consistently fosters innovation responsibly.
How Can You Improve Your Artificial Intelligence Proficiency?
AI skills, such as making money with AI chatbots, require specialized skills that are best honed through rigorous, strategic efforts. Even those looking for high-school diploma jobs like AI assistants can become proficient by dedicating time to building expertise.
Start by learning the fundamentals of math, stats, and programming. Then, take online courses in machine learning, deep learning, and advanced AI from leading institutions. Additionally, actively read research papers and case studies to be updated on the latest innovations.
Work on Kaggle competitions, GitHub projects, and portfolio demos to gain practical experience. Participate in workshops and seminars to connect with experts. Join online developer communities for troubleshooting and collaboration opportunities.
Finally, keep practicing and apply learnings to solve real-world problems. Follow this blueprint to accelerate your AI skills journey.
Final Note
The astounding pace at which artificial intelligence is evolving presents a huge opportunity today. You should skill up for high-potential careers in this space. Thankfully, you now have all the guidance needed to smartly enhance technical know-how and even land jobs without any experience.
With persistence and passion for learning, anyone can excel in AI over time. So, let’s get started on your rewarding AI journey today towards a bright future built on purposeful innovation!
Zeeshan Hakmi, CEO of FinancingFocus.com, has been causing a stir in the software development world for over two decades. Armed with an MBA from Governors State University and a knack for problem-solving, this new-age entrepreneur has been leading the charge in User Acceptance Testing (UAT) and project delivery across the USA.
When he’s not busy exploring the limitless potential of artificial intelligence, you can find him penning thought-provoking articles on the intersection of AI, business, and finance. But don’t let his tech-savvy persona fool you – Zeeshan is a nature enthusiast at heart, always ready to trade his keyboard for a hiking trail.
With a passion for innovation and a thirst for adventure, Zeeshan is proof that you can have your code and travel too.