AI has already started to change the world we live in. We now have access to artificial intelligence tools that are making certain areas of work and life faster and more productive. The pace of change is startling, making many more people want to learn AI.
We’ve already seen the importance of AI. We have found that 62% of leaders believe that AI literacy is important for their teams’ daily tasks. Professionals in all kinds of industries are
using generative AI tools like ChatGPT, Midjourney, and Gemini to change their workflows. As such, the art and science of AI are more relevant today than ever before.
Whether you want to become a data scientist, a machine learning engineer, an AI researcher, or you’re simply an AI enthusiast, this guide is for you. We’ll cover how to learn AI from scratch and provide practical advice and tips from industry experts to help your learning journey. As well as covering the skills and tools you need to master, we’ll also explore how businesses can use AI to be more productive.
The IT sector is poised for continued expansion, with projections indicating significant growth by 2030. According to the Future of Jobs Report 2025, technological advancements, particularly in AI and digital access, are expected to transform the global labor market, with 60% of employers anticipating business transformation by 2030 due to broadened digital access. Specific roles in high demand include AI engineers, data scientists, cybersecurity specialists, and cloud developers, as noted in 2025 In-Demand Technology Roles, where unemployment rates for IT roles like software developers (2.2%) and security analysts (1.4%) are well below the national average of 4.1% in Q4 2024.
Management roles are also evolving, with a strong emphasis on soft skills. The 9 Trends That Will Shape Work in 2025 and Beyond highlights challenges for leaders, including new demands for future-ready workforces and evolving manager roles, requiring skills in collaboration, human resource management, and organizational transformation. Reports like IT Job Trends: Top 7 Tech Jobs Trends to Watch in 2025 project a 5.3% annual growth in the global tech industry, with a 20% surge in demand for specialized roles, underscoring the need for continuous learning and adaptability.
An interesting aspect is the focus on workload management to prevent burnout, as seen in State of IT Jobs, where 48% of tech workers report increased burnout due to heavy workloads, potentially leading to higher turnover rates, especially among younger workers aged 25-35. This trend is particularly relevant as companies adapt to hybrid work models, with flexibility becoming a key factor in employee retention, as noted in Job Market Outlook 2025.
AI is a broad field with several subsets, including Machine Learning (ML) and Deep Learning (DL).
While there isn’t an official definition for any of these terms, and while experts argue over the exact boundaries, there is a growing consensus on the broad scope of each term. Here’s a breakdown of these terms:
Data science is a cross-disciplinary field that uses all of the above, amongst other skills like data analysis, statistics, data visualization, and more, to get insight from data.
Artificial Intelligence isn’t the future; it’s the present. The number of AI jobs has seen significant growth over recent years. According to the World Economic Forum’s Future of Jobs report, AI and machine learning specialists top the list of fast-growing jobs over the next five years. As
industries continue to adopt AI technologies to streamline their operations and make better decisions, the demand for AI specialists will likely only increase.
Statista statistics project considerable AI market size growth, further emphasizing this point. They estimate that the market size in Artificial Intelligence will reach US$243.72bn in 2025 and US$826.73bn by 2030.
AI is a rapidly evolving field. Once you get the basics, it’s important to keep learning and improving your skills. Follow AI blogs, read research papers, take advanced courses, and always be on the lookout for new ways to challenge yourself. This iterative process will turn you from a novice into an expert.
Remember, the journey to learning AI is challenging but immensely rewarding. Don’t get discouraged if you encounter obstacles along the way; they’re part of the learning process. Keep your end goal in mind, and stay committed to your journey.
Data Scientist | Machine Learning Engineer | Research Scientists | |
What is it? | Extracts and reports meaningful insights from data to solve business problems. | Designs and deploys machine learning systems to make predictions from data. | Conducts research to advance the state-of-the-art in AI. Publishes findings. |
Key Skills | Extracts and reports meaningful insights from data to solve business problems. | Python, Java, Scala, ML Frameworks, Data Structures, Software Architecture, Mathematics, Teamwork, Problem-solving | ML, Deep Learning, Programming, AI-related Math, Conceptualization, Writing, Public Speaking |
Tools | Pandas, NumPy, Scikit-learn, Matplotlib, Tableau, Airflow, Spark, Git, Bash | Scikit-learn, TensorFlow, Pandas, NumPy, AWS, Google Cloud Platform, Git | TensorFlow, PyTorch, MatLab, Mathematica, LaTeX, Google Slides, WS, Google Cloud Platform |
A degree can be a great asset when starting a career in AI, but it’s not the only pathway. While we do think it’s worthwhile to get a formal education in AI or an adjacent field, more and more professionals are entering the field through non-traditional routes, proving that with dedication, consistent learning, and a proactive approach, you can land your dream job in AI.
Learning AI is a rewarding pursuit that opens doors to a world of innovative technologies and exciting career opportunities. The knowledge and expertise gained through this process go beyond textbooks and lectures. It involves a dynamic cycle of learning, applying, experimenting, and improving. Embracing a hands-on approach, particularly through courses and AI projects, accelerates learning and cultivates essential skills in problem-solving, critical thinking, and creativity.
If you’re just starting out on your AI learning journey, we’ve outlined loads of helpful resources to help you get started, as well as an example learning plan for some of the key themes you’ll need to master on your way to become proficient in artificial intelligence. Get started today with our Understanding AI Course.
