5 answers
Buhle
Student
Sebokeng, Gauteng, South Africa
1
Question
Updated
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How did I enter the AI industry ?
I'm a South African studying IT and would like to know how to land a career as an AI engineer
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5 answers
Michelle M.
Actress
3276
Answers
Updated
Michelle’s Answer
Hello, Buhle !
If you want to become an Artificial Intelligence engineer, you will have to either go to a university that offers the Bachelors Degree or Masters Degree in AI. You would get full training for that career that way. There are some universities in South Africa that do offer programs in AI.
Some of the Universities in South Africa that you can look further into for Majoring in Artificial Intelligence are Stellenbosch University, The University of the Witwatersrand, The University of Cape Town has courses in AI within its' Computer Science Major, The University of Pretoria has AI courses for Computer Science Majors, North-West University offers a Master of Science in Computer Science with a specialization in AI. The University of Johannesburg provides a BSc in Computer Science and Informatics specializing in AI, as well as a Master of AI.
While you may be able to take courses in Artificial Intelligence during a Bachelors Degree path, it seems that these courses are contained in the curriculum for Computer Science Majors, so you can consider taking a Major in Computer Science at University.
For the best accurate information about this, visit some of the Universities and inquire about the programs. You can first see if any of the Universities I have mentioned have websites and see if the information about AI courses is mentioned.
The common names of the career position you want are AI Developer, AI Engineer, or Machine Learning Engineer. In order to have this career, you will need to know how to do coding, testing, and integrating AI models into applications, requiring proficiency in programming languages like Python, Java, and C++. An AI Engineer, on the other hand, emphasizes the engineering, optimization, and deployment of AI systems, requiring expertise in cloud computing, infrastructure management, and system scalability. So it all depends on exactly what work you want to do. It seems as though obtaining a Bachelors Degree in Computer Science first and then a Masters in AI or close subject would be the path for you to go in your country.
Explore this first hand for a lot more information. You can visit or contact the schools or meet with an academic advisor at your secondary school.
Best wishes in all you do !
If you want to become an Artificial Intelligence engineer, you will have to either go to a university that offers the Bachelors Degree or Masters Degree in AI. You would get full training for that career that way. There are some universities in South Africa that do offer programs in AI.
Some of the Universities in South Africa that you can look further into for Majoring in Artificial Intelligence are Stellenbosch University, The University of the Witwatersrand, The University of Cape Town has courses in AI within its' Computer Science Major, The University of Pretoria has AI courses for Computer Science Majors, North-West University offers a Master of Science in Computer Science with a specialization in AI. The University of Johannesburg provides a BSc in Computer Science and Informatics specializing in AI, as well as a Master of AI.
While you may be able to take courses in Artificial Intelligence during a Bachelors Degree path, it seems that these courses are contained in the curriculum for Computer Science Majors, so you can consider taking a Major in Computer Science at University.
For the best accurate information about this, visit some of the Universities and inquire about the programs. You can first see if any of the Universities I have mentioned have websites and see if the information about AI courses is mentioned.
The common names of the career position you want are AI Developer, AI Engineer, or Machine Learning Engineer. In order to have this career, you will need to know how to do coding, testing, and integrating AI models into applications, requiring proficiency in programming languages like Python, Java, and C++. An AI Engineer, on the other hand, emphasizes the engineering, optimization, and deployment of AI systems, requiring expertise in cloud computing, infrastructure management, and system scalability. So it all depends on exactly what work you want to do. It seems as though obtaining a Bachelors Degree in Computer Science first and then a Masters in AI or close subject would be the path for you to go in your country.
Explore this first hand for a lot more information. You can visit or contact the schools or meet with an academic advisor at your secondary school.
Best wishes in all you do !
Teklemuz Ayenew Tesfay
Electrical Engineer, Software Developer, and Career Mentor
517
Answers
Ethiopia
Updated
Teklemuz Ayenew’s Answer
Build a strong IT foundation and take electives in AI, machine learning, or data analytics if available. Learn Python and core AI/ML concepts through Kaggle Learn, fast.ai, and free or audited courses on Coursera and edX. Apply your skills by creating personal projects, experimenting with real datasets in Google Colab, and showcasing your work on GitHub. Gain practical experience through labs, workshops, hackathons, conferences, university clubs, and local or virtual meetups.
Hands-on practice is essential. Engage in Kaggle competitions, contribute to open-source AI projects, and explore virtual or project-based programs. Master tools such as NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch, and earn digital badges from IBM SkillsBuild to strengthen your profile. Pursue internships at Zibuza AI, the Foschini Group, PrimeSETA, or Sanlam to gain industry experience, and network actively on LinkedIn, Stack Overflow, Discord, Slack, Reddit, and Kaggle communities.
Equally important are soft skills: stay curious and updated on AI trends, develop strong problem-solving abilities, and communicate your ideas effectively. Combining a strong IT foundation, structured learning, hands-on projects, volunteering, internships, community engagement, and key soft skills builds the expertise, credibility, and connections needed for entry-level AI roles.
Hands-on practice is essential. Engage in Kaggle competitions, contribute to open-source AI projects, and explore virtual or project-based programs. Master tools such as NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch, and earn digital badges from IBM SkillsBuild to strengthen your profile. Pursue internships at Zibuza AI, the Foschini Group, PrimeSETA, or Sanlam to gain industry experience, and network actively on LinkedIn, Stack Overflow, Discord, Slack, Reddit, and Kaggle communities.
Equally important are soft skills: stay curious and updated on AI trends, develop strong problem-solving abilities, and communicate your ideas effectively. Combining a strong IT foundation, structured learning, hands-on projects, volunteering, internships, community engagement, and key soft skills builds the expertise, credibility, and connections needed for entry-level AI roles.
Rebecca Aidoo
Fashion specialists
20
Answers
Accra, Greater Accra Region, Ghana
Updated
Rebecca’s Answer
It’s great to know that you’re leveling up your skills in IT. However, to land a job as an AI engineer, you first need to identify the specific type of AI engineer you want to become whether that’s a Machine Learning Engineer, Data Scientist, Robotics Engineer, or AI Systems Engineer. Each path requires a different focus and skill set.
Once you’ve made that decision, you can begin taking relevant online certification courses to build your skills and gain the foundational knowledge required for your chosen area. Beyond certifications, it’s important to apply what you learn through hands-on projects, working with real datasets, and solving practical problems.
To further deepen your understanding and expertise, pursuing a master’s degree in artificial intelligence, data science, or a related field can be highly beneficial. Networking with industry professionals, attending tech events and conferences also provides valuable exposure. Additionally, volunteering, internships, or junior roles aligned with your career goals offer real-world experience and strengthen your professional profile. Consistency, continuous learning, and practical exposure are key to building a successful career in AI engineering.
Once you’ve made that decision, you can begin taking relevant online certification courses to build your skills and gain the foundational knowledge required for your chosen area. Beyond certifications, it’s important to apply what you learn through hands-on projects, working with real datasets, and solving practical problems.
To further deepen your understanding and expertise, pursuing a master’s degree in artificial intelligence, data science, or a related field can be highly beneficial. Networking with industry professionals, attending tech events and conferences also provides valuable exposure. Additionally, volunteering, internships, or junior roles aligned with your career goals offer real-world experience and strengthen your professional profile. Consistency, continuous learning, and practical exposure are key to building a successful career in AI engineering.
Sandeep Khandelwal
Software Engineer
50
Answers
San Ramon, California
Updated
Sandeep’s Answer
Hello Buhle,
I entered the AI industry by first building a strong foundation in programming and core computer science concepts, especially Python, data structures, and basic machine learning. Instead of rushing into advanced AI topics, I focused on understanding how models work, practicing with small projects, and applying what I learned to real problems. Online courses, hands-on labs, and consistent practice played a big role in building confidence.
To land a career as an AI engineer today, I’d recommend starting with Python, math basics (statistics and linear algebra), and machine learning fundamentals, then slowly moving into deep learning and practical AI tools. Work on real projects like prediction models, chatbots, or simple computer vision apps and share them on GitHub/Bitbucket. Even as a student in South Africa, you can access global opportunities through remote roles, open-source contributions, and internships skills matter more than location if you can show what you’ve built.
I entered the AI industry by first building a strong foundation in programming and core computer science concepts, especially Python, data structures, and basic machine learning. Instead of rushing into advanced AI topics, I focused on understanding how models work, practicing with small projects, and applying what I learned to real problems. Online courses, hands-on labs, and consistent practice played a big role in building confidence.
To land a career as an AI engineer today, I’d recommend starting with Python, math basics (statistics and linear algebra), and machine learning fundamentals, then slowly moving into deep learning and practical AI tools. Work on real projects like prediction models, chatbots, or simple computer vision apps and share them on GitHub/Bitbucket. Even as a student in South Africa, you can access global opportunities through remote roles, open-source contributions, and internships skills matter more than location if you can show what you’ve built.
Maria Gabriella Mittiga
Localization Program Manager
3
Answers
Portland, Oregon
Updated
Maria Gabriella’s Answer
Hi Buhle, you might have already some skills since you are an IT student, logical mind set and troubleshooting. These below are the three pillars for AI industry:
Python Proficiency: This is the industry standard.
Mathematics: you must understand Linear Algebra, Calculus (how models learn/optimize), and Probability/Statistics (how models handle uncertainty).
Data Engineering: "Data is the new code." Learn SQL and how to build ETL (Extract, Transform, Load) pipelines to feed clean data into your systems.
If it is possible for you to attend a Computer Science degree will be the best otherwize start with some Python classes and SQL classes.
Good luck in you career!
Python Proficiency: This is the industry standard.
Mathematics: you must understand Linear Algebra, Calculus (how models learn/optimize), and Probability/Statistics (how models handle uncertainty).
Data Engineering: "Data is the new code." Learn SQL and how to build ETL (Extract, Transform, Load) pipelines to feed clean data into your systems.
If it is possible for you to attend a Computer Science degree will be the best otherwize start with some Python classes and SQL classes.
Good luck in you career!