Generative AI Specialisation Courses from IBM for Every Profession

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You’re probably in your role and wondering how you can upskill with the new Generative AI boom. Well, don’t you worry, the team at KDnuggets have you set. The AI space is moving faster than we can blink—specifically Generative AI.

A lot of us are using Generative AI in our everyday workflows, as well as personal. However, if you are interested in how you can upskill, make use of generative AI and most importantly feel like your job is not at risk, the best thing you can do is learn about it.

In this blog, I will go through a range of generative AI specialisation courses for specific professions.

Generative AI for Data Analysts

 
Link: Generative AI for Data Analysts

The way organisations make decisions using generative AI is on the rise. Therefore, as a data analyst, it is your responsibility to understand how generative AI data analysis can improve your organisation.

In this specialisation course offered by IBM, you will learn about real-world generative AI use cases and popular generative AI models and tools for text, code, image, audio, and video generation. You will delve into generative AI prompts engineering concepts, using prompt techniques such as zero-shot and few-shot and explore various prompt engineering approaches, and tools like IBM Watson, Prompt Lab, Spellbook, and Dust.

You will then move on to enhancing your knowledge by understanding the building blocks and foundation models of generative AI, such as the GPT, DALL-E, and IBM Watson Studio along with the ethical implications, considerations, and challenges while using generative AI in different industries.

Generative AI for Cybersecurity

 
Link: Generative AI for Cybersecurity

I believe Cybersecurity doesn’t get as much love as it should. They are the masterminds behind securing an organisation to ensure that it can effectively operate. As a cyber security professional, learning generative AI skills is essential to your everyday toolkit.

In this specialisation course offered by IBM, you will start by distinguishing the difference between generative AI and discriminative AI. You will then dive in and explore real-world generative AI use cases and discover popular generative AI models. You will also delve into generative AI prompts engineering concepts. Last but not least, you will learn the fundamental concepts of generative AI use for cybersecurity and how to apply generative AI techniques to real-world scenarios, including UBEA, threat intelligence, report summarisation, and playbooks, and assess their impact and vulnerabilities.

Generative AI for Data Engineers

 
Link: Generative AI for Data Engineers

As a data engineer, your roles and responsibilities are around efficient data collection, generation, transformation and storage. With the help of generative A, you can use tools that have the capability of making each of the data engineering tasks more efficient, effective, and convenient on an ETL pipeline.

This IBM specialisation course is designed not only for Data Engineers but for anyone who might be interested in the use of generative AI in Data Engineering. With three self-paced courses in the specialisation, you will begin with learning the differences that distinguish generative AI from discriminative AI. You’ll delve into real-world generative AI use cases and explore popular generative AI models and tools for text, code, image, audio, and video generation. Last but not least, learn about prompt techniques like zero-shot and few-shot and explore various prompt engineering approaches and explore commonly used prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust.

Generative AI for Software Developers

 
Link: Generative AI for Software Developers

As a software developer in this day and age, there is so much that you can leverage from this revolutionary technology of generative AI, for example, writing high-quality code with fewer bugs. Generative AI for software developers has been shown to increase their overall effectiveness and efficiency – making generative AI an essential and must-have skill for software engineers.

This IBM specialisation course is for those in the software development sector who are interested in leveraging the power of generative AI in their day-to-day workflow. However, this is not only for software developers, this also includes existing and aspiring web developers, mobile app developers, front-end developers, back-end developers, full stack developers, DevOps professionals, and Site Reliability Engineers (SREs).

In this specialisation, you will begin with the basics of generative AI including its uses, models, and tools for text, code, image, audio, and video generation. Advance to prompt engineering, explore various prompt engineering approaches and prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust.

Generative AI for Product Managers

 
Link: Generative AI for Product Managers

Want some assistance with building, launching and delivering your products to the market? As product managers, you can use generative AI to help offload some of your tasks, if it be task automation or user experience personalisation, generative AI can help with design and development in the product pipeline.

This IBM specialisation will help Product Managers, regardless if they’re new or experienced, become well-versed with generative AI and gain insights on how to leverage this technology to their advantage. You will begin with how to distinguish generative AI from discriminative AI and then delve into real-world generative AI use cases and explore popular generative AI models.

You will then master generative AI prompts engineering concepts for real-world business uses. Learn about prompt techniques like zero-shot and few-shot, various prompt engineering approaches, and tools including IBM Watsonx and Spellbook. Last but not least, you will explore specific generative AI techniques and processes that product managers can use to deliver better products in shorter time frames.

Wrapping up

 
5 different specialisation courses, for 5 different jobs. Although the content of these specialisation courses is very similar, the major difference is how it tailors to the specific job title, ensuring that you as the learner get the most out of it and can apply it to your day-to-day workflow.
 
 

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.