Overview
Class Central Tips
The demand for professionals with a knowledge of artificial intelligence (AI) is on the rise. There is a revolution in the way organizations make decisions on the basis of generative AI data analysis. This specialization brings forth real-world generative AI use cases and popular generative AI models and tools for text, code, image, audio, and video generation.
In this specialization, you will delve into generative AI prompts engineering concepts and real-world business uses. Learn about prompt techniques like zero-shot and few-shot and explore various prompt engineering approaches, and tools like IBM Watsonx, Prompt Lab, Spellbook, and Dust.
Next enhance your skills with an in-depth knowledge of the fundamental concepts, models, tools, and generative AI applications, with regards to the data analytics landscape. Learn about the building blocks and foundation models of generative AI, such as the GPT, DALL-E, and IBM Watson Studio. Additionally, you will understand the ethical implications, considerations, and challenges while using generative AI in different industries.
The hands-on labs included in the course offer an opportunity to apply different tools in the IBM Generative AI Classroom. You will apply the concepts learned in the course in a real-life project scenario at the end of the course.
No experience is needed to begin this specialization, although you might find it helpful to have some data analytics knowledge.
Syllabus
Course 1: Generative AI: Introduction and Applications
- Offered by IBM. This course is designed for everyone, including professionals, executives, students, and enthusiasts, interested in learning ... Enroll for free.
Course 2: Generative AI: Prompt Engineering Basics
- Offered by IBM. This course is designed for everyone, including professionals, executives, students, and enthusiasts interested in ... Enroll for free.
Course 3: Generative AI: Enhance your Data Analytics Career
- Offered by IBM. This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth ... Enroll for free.
- Offered by IBM. This course is designed for everyone, including professionals, executives, students, and enthusiasts, interested in learning ... Enroll for free.
Course 2: Generative AI: Prompt Engineering Basics
- Offered by IBM. This course is designed for everyone, including professionals, executives, students, and enthusiasts interested in ... Enroll for free.
Course 3: Generative AI: Enhance your Data Analytics Career
- Offered by IBM. This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth ... Enroll for free.
Courses
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This course is designed for everyone, including professionals, executives, students, and enthusiasts interested in leveraging effective prompt engineering techniques to unlock the full potential of generative artificial intelligence (AI) tools like ChatGPT. Prompt engineering is a process to effectively guide generative AI models and control their output to produce desired results. In this course, you will learn the techniques, approaches, and best practices for writing effective prompts. You will learn about prompt techniques like zero-shot and few-shot, which can improve the reliability and quality of large language models (LLMs). You will also explore various prompt engineering approaches like Interview Pattern, Chain-of-Thought, and Tree-of-Thought, which aim at generating precise and relevant responses. You will be introduced to commonly used prompt engineering tools like IBM watsonx Prompt Lab, Spellbook, and Dust. The hands-on labs included in the course offer an opportunity to optimize results by creating effective prompts in the IBM Generative AI Classroom. You will also hear from practitioners about the tools and approaches used in prompt engineering and the art of writing effective prompts.
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This course is designed for everyone, including professionals, executives, students, and enthusiasts, interested in learning about generative AI and leveraging its capabilities in their work and lives. This course is your first step toward understanding the capabilities of generative AI, powered by different models, including large language models (LLMs). In this course, you will learn about the fundamentals and evolution of generative AI. You will explore the capabilities of generative AI in different domains, including text, image, audio, video, virtual worlds, code, and data. You will understand the applications of generative AI across different sectors and industries. You will learn about the capabilities and features of common generative AI models and tools, such as GPT, DALL-E, Stable Diffusion, and Synthesia. Hands-on labs, included in the course, provide an opportunity to explore the use cases of generative AI through IBM Generative AI Classroom and popular tools like ChatGPT. You will also hear from the practitioners about the capabilities, applications, and tools of generative AI.
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This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth knowledge of the fundamental concepts, models, tools, and generative AI applications regarding the data analytics landscape. In this course, you will examine real-world applications and use generative AI to gain data insights using techniques such as prompts, visualization, storytelling, querying and so on. In addition, you will understand the ethical implications, considerations, and challenges of using generative AI in data analytics across different industries. You will acquire practical experience through hands-on labs where you will leverage generative AI models and tools such as ChatGPT, ChatCSV, Mostly.AI, SQLthroughAI and more. Finally, you will apply the concepts learned throughout the course to a data analytics project. Also, you will have an opportunity to test your knowledge with practice and graded quizzes and earn a certificate. This course is suitable for both practicing data analysts as well as learners aspiring to start a career in data analytics. It requires some basic knowledge of data analytics, prompt engineering, Python programming and generative artificial intelligence.
Taught by
Abhishek Gagneja, Antonio Cangiano, Dr. Pooja and Rav Ahuja