Generative AI is on the loose, getting into business and commerce as well as into art, poetry and coding. Already useful, it will become ever more useful as long as we use it properly. Coursera has training for everybody - and for developers and data scientists in particular.
Coursera launched a Generative AI Academy in January. As with its other academies covering Leadership, Marketing, Finance and so on, it's part of Coursera For Business aimed at helping companies train their workforce.
The mission of the new Generative AI Academy is to:
Build Generative AI skills across your entire organization
and this includes the upper echelons.
There are currently two courses aimed specifically at business leaders. Generative AI for Leaders is from Vanderbilt University, taught by Dr Jules White. Its three modules are:
Introduction to Generative AI
Using Generative AI as a Leader
Addressing Staff Anxiety: Augmented Intelligence, Not Artificial Intelligence
Their video content totals less than 2 hours in total. However, to earn the certificate there's a three hour graded assessment. If you don't want to do the assessment you can audit this course for free, and can do so even if you are not a business leader.
The other course on Generative AI for top management, Navigating Generative AI: A CEO Playbook, comes from Coursera itself with Jeff Maggioncalda, CEO of Coursera as its lead instructor. It has four modules:
The role of the CEO in navigating GenAI (1 hour, 9 videos, 1 ungraded lab, 1 assignment)
Setting a generative AI strategy (1 hour, 4 videos, 5 ungraded labs, 1 assignment)
Empowering and transforming your organization with GenAI (33 mins, 4 videos, 1 assignment)
Navigating Generative AI risks for leaders (39 mins, 3 videos, 2 readings, 1 assignment)
As explained in the Welcome video:
this course is a condensed version of our more comprehensive four course specialization that we call navigating generative AI for leaders. This summary course is designed for leaders seeking a dense yet insightful entry into the world of generative AI. If you're pressed for time but eager to start, this is the perfect place for you. All progress that you make here can seamlessly transfer into the more comprehensive specialization, if you want to dive deeper later on.
Maggioncalda is referring to the Navigating Generative AI for Leaders Specialization. This is comprised of four courses with the same titles as for the CEO Playbook with extra content and assignments and requiring 15 hrs in total.
The learning outcomes are also the same:
A practical overview of GenAI’s capabilities, limitations, and where it may be heading
How to use GenAI as a "thought partner” to set strategy, improve decision-making, analyze competition, and communicate more effectively
How to enable your organization to use GenAI to create customer value and boost productivity
How to move quickly and safely with an understanding of the risks associated with this technology
Coursera has another specialization in Generative AI which comes from IBM and has been tailored for different audiences. The core version is Generative AI Fundamentals Specialization. At Beginner level, and included in Coursera Plus, it is intended to take 3-6 monthsand its learning outcomes are:
Explain the fundamental concepts, capabilities, models, tools, applications, and platforms of generative AI foundation models.
Apply powerful prompt engineering techniques to write effective prompts and generate desired outcomes from AI models.
Discuss the limitations of generative AI and explain the ethical concerns and considerations for the responsible use of generative AI.
Recognize the ability of generative AI to enhance your career and help implement improvements at your workplace.
It consists of 5 courses taught by Rav Ahuja and Antonio Cangiano:
Introduction and Applications - 6 hours
Prompt Engineering Basics - 7 hours
Foundation Models and Platforms - 6 hours
Impact, Considerations, and Ethical Issues - 5 hours
Business Transformation and Career Growth - 5 hours
Each course has three modules, the final one of which is its Course Quiz, Project and Wrap up.
The variations on this Specialization are at Intermediate Level and consist of the first two courses list above with a third course specific to Cybersecurity, Data Analytics, Data Science, Software Development/DevSecOps respectively.
Data Science and Generative AI This module explores the role of generative AI in data science and looks at the four common types of generative AI models and their impact and applications across diverse industries. It shows how data scientists can leverage generative AI in the data science lifecycle.
Use of Generative AI for Data Science Learn how data scientists can use generative AI to visualize, develop, and build models and the use of generative AI for data science regarding tools and techniques to help in exploratory data analysis (EDA) and develop a predictive model. Learn about the industry-specific considerations while using generative AI and the challenges data scientists face. You will also learn about the skills data scientists require to succeed in their field and how generative AI can help them hone those skills in today’s world.
Exam module - 2 hours to complete the guided project and evaluation.
Learn how AI impacts software development. Understand how to leverage AI for the software development lifecycle using various tools and algorithms and set up a development environment for AI and ChatGPT. You will also learn about LLMs, transformers, and NLP and use them to create a chatbot. Explore the best practices and design patterns using AI for technical help and software architecture. You will learn how AI helps with code generation, bug detection, and troubleshooting and list the useful AI prompts for software development. Also covers the use of AI to generate static websites and architecture diagrams.
Generative AI for Software Development Workflows and its Considerations
Learn how to use AI for DevSecOps, software testing, and Generative AI considerations and the nuances of using AI for CI/CD and software security using AI tools. You will learn how to generate test cases for specific use cases using AI. You will also understand the integration of AI into software development workflows. Explore the ethical considerations for software development in AI and innovation with Generation AI and explore some of the useful prompts for software testing and DevOps.
Exam Module - 4 hours to complete a final project where you will have an opportunity to demonstrate your proficiency in building personalized learning for developers and the final exam will test your knowledge of the course’s content including the essential concepts and their application.
Gaining a certificate that confirms your understanding of Generative AI for your specific job role seems like a worthwhile investment of your time and effort - and should also boost your productivity. A win-win situation.
Google has added a premium tier to the Google Developer Program. The new tier is described as providing "a tailored suite of services to help developers throughout the learning, building and deploymen [ ... ]
Findings from GitHub show that code authored with Copilot has increased functionality and improved readability, is of better quality, and receives higher approval rates than code authored without it.
