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You are probably in your role and wondering how you can improve yourself with the new boom of generative AI. Well, don’t worry, the KDnuggets team has you prepared. The field of AI is evolving faster than we can blink, especially generative AI.
Many of us are using generative AI in our daily workflows, as well as in our personal lives. However, if you want to know how you can improve your skills, use generative AI, and most importantly feel like your job is not in danger, the best thing to do is to learn more.
In this blog, I will review a range of generative AI specialization courses for specific professions.
Generative AI for Data Analysts
Link: Generative AI for Data Analysts
Organizations are increasingly using generative AI to make decisions. Therefore, as a data analyst, it is your responsibility to understand how generative AI data analysis can improve your organization.
In this IBM specialization course, you will learn real-world use cases for generative AI and popular generative AI models and tools for generating text, code, images, audio, and video. You will dive into generative AI prompt engineering concepts, using prompting techniques such as zero-shot and few-shot, and explore various prompt engineering approaches and tools such as IBM Watson, Prompt Lab, Spellbook, and Dust.
You will then move on to enhancing your knowledge by understanding the building blocks and fundamental models of generative AI, such as GPT, DALL-E, and IBM Watson Studio, as well as the ethical implications, considerations, and challenges of using generative AI in different industries.
Generative AI for Cybersecurity
Link: Generative AI for Cybersecurity
I think cybersecurity is underappreciated. They are the brains that are responsible for securing an organization to ensure its proper functioning. As a cybersecurity professional, learning generative AI skills is essential to your daily toolbox.
In this IBM specialization course, you will start by distinguishing the difference between generative AI and discriminative AI. You will then explore real-world generative AI use cases and learn about popular generative AI models. You will also dive into the concepts of generative AI prompt engineering. Finally, you will learn the fundamental concepts of using generative AI for cybersecurity and how to apply generative AI techniques to real-world scenarios, including UBEA, threat intelligence, report synthesis, 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 involve the efficient collection, generation, transformation, and storage of data. With the help of Generative A, you can use tools that can make each of the data engineering tasks more effective, efficient, and convenient on an ETL pipeline.
This IBM Specialization course is designed not only for data engineers, but for anyone who might be interested in using generative AI in data engineering. With three self-paced courses in the Specialization, you will start by learning the differences between generative AI and discriminative AI. You will dive into real-world generative AI use cases and explore popular generative AI models and tools for generating text, code, images, audio, and video. Finally, learn about prompting techniques such as 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, you can now take advantage of many opportunities offered by this revolutionary technology called generative AI, such as 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 a critical and must-have skill for software engineers.
This IBM specialization course is designed for software development professionals who want to harness the power of generative AI in their daily workflow. However, it is not only for software developers, but also for existing and aspiring web developers, mobile application developers, front-end developers, back-end developers, full-stack developers, DevOps professionals, and Site Reliability Engineers (SREs).
In this specialization, you will start with the basics of generative AI, including its uses, models, and tools for generating text, code, images, audio, and video. Moving on to prompt engineering, you will 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
Need help creating, launching, and distributing your products to market? As product managers, you can use generative AI to help offload some of your tasks. From automating tasks to personalizing the user experience, generative AI can help you design and develop the product pipeline.
This IBM Specialization will help both new and experienced product managers get started with generative AI and understand how to leverage the technology to their advantage. You’ll start by distinguishing generative AI from discriminative AI, then dive into real-world generative AI use cases and explore the most popular generative AI models.
You’ll then master the concepts of engineering generative AI prompts for real-world business uses. Learn about prompting techniques like zero-shot and few-shot, various prompt engineering approaches, and tools like IBM Watsonx and Spellbook. Finally, you’ll explore specific generative AI techniques and processes that product managers can use to deliver better products in faster timeframes.
To conclude
5 different specialization courses, for 5 different professions. Although the content of these specialization courses is very similar, the main difference is in how it is adapted to the specific position, ensuring that you, as a learner, get the most out of it and can apply it to your daily work.
Nisha Arya Nisha is a data scientist, freelance technical writer, editor, and community manager for KDnuggets. She is particularly interested in providing career advice or data science tutorials and theoretical knowledge around data science. Nisha covers a wide range of topics and wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. Passionate about learning, Nisha seeks to expand her technical knowledge and writing skills, while helping guide others.
