Generative AI for Software Development from DeepLearning.AI | Recap & Review

DeepLearning.AI recently (and we mean RECENTLY-- the course launched last week) partnered with Google Cloud to develop a brand new course, Generative AI for Software Development. The curriculum aims to equip learners with the skills necessary to leverage generative AI in modern software development. With the rapidly expanding role of AI in tech, this course provides a strong foundation for developers interested in integrating AI into their workflows. Note: we thought the professor for this course was quite impressive. The lessons are developed and taught by Laurence Moroney, former AI lead at Google and big-time AI educator. What a great get for Coursera!

Best for: Junior to Mid-Level Engineers

This course is heavily focused on AI-beginners, but not engineering beginners! The course recommends a familiarity with a few concepts, including Python, algorithms, and various software development concepts.

Program Highlights

• Sponsored Institution: DeepLearning.AI and Google Cloud
• Course Duration: Approximately 1 month (at 5 hours/week, but it's move-at-you-own-pace)
• Skill Level: Beginner to Intermediate, however some engineering familiarity is needed!
• Rating: No ratings! It's brand new.
• Cost: Free 7-day trial, then $49/month

Who Should Take This Course?

This course is best suited for:

• Junior or aspiring software developers interested in expanding their AI knowledge
• Intermediate programmers looking to implement AI models in real-world applications
• Adjacent professionals (think: product managers, analysts, etc) aiming to stay competitive in the evolving tech landscape

If you have a strong foundation in coding (Python in particular) and an understanding of machine learning basics, you'll find this course especially beneficial. While beginners in AI are welcome, having prior experience in software development will make it easier to grasp the more advanced concepts. If you're looking for a true beginner course, we recommend Stanford's Machine Learning Specialization!!

We recapped the learning objectives from each week to set your expectations for course material. The great part about this certification is that it's self-paced-- meaning that if you're super determined you can likely knock it out in a weekend. However, we've recapped the material in weekly chunks for you here. The primary focus of the entire cert is teaching the different types of engagements you can have while prompting the AI. Each week mostly focuses on the different themes-- we found this format to be incredibly helpful and thoughtful provoking.

Course 1: Introduction to Generative AI for Software Development

Time to Complete: 8 hours

General Concepts:
This course introduces the foundational concepts of generative AI and how it can be applied to software development. You'll explore how generative AI tools can enhance efficiency, from design to deployment, and learn how to use LLMs to improve coding processes and productivity.

Skills You'll Learn:

• Prompting best practices for software development
• Assigning an LLM a role or persona
• Designing data structures for real-world deployment at scale
• Analyzing code with LLMs
• Pair-coding with LLMs

Course 2: Team Software Engineering with AI

Time to Complete: 13 hours

General Concepts:
In this course, you’ll dive into how generative AI can transform collaborative software engineering processes. Learn how to integrate AI-driven tools into team workflows to boost collaboration, automate repetitive tasks, and improve overall code quality. The course also covers AI-powered pair programming and how to use AI for team-based software development in real-world environments.

Skills You'll Learn:

• Collaborative software development with AI
• Automating repetitive coding tasks using AI
• AI-driven pair programming
• Best practices for integrating AI into team workflows

Course 3: AI-Powered Software and System Design

Time to Complete: 11 hours

General Concepts:
This course focuses on applying generative AI to software and system design. You’ll learn how to leverage AI tools for creating scalable, reliable, and efficient software architectures. The course emphasizes how AI can enhance decision-making during the design phase and improve system performance through continuous AI-driven optimizations.

Skills You'll Learn:

• Designing software systems with AI assistance
• AI-powered decision-making in system architecture
• Creating scalable and efficient software designs
• Monitoring and optimizing system performance using AI

The certificate is only $49/month, so theoretically (if you're determined) should only be about $50. But maybe assume you'll take some breaks, so it'll be around $100. Totally worth it, in our opinion.

If you have a learning budget at your current company, or are dedicated to upskilling your career into something engineering related– we recommend completing the certificate and getting the shareable certificate (GET RECEIPTS!). This will help make your Linkedin and resume more searchable to recruiters who may be looking for specific keywords and programs. To audit the program and simply learn the material, this program is completely free. Learn more about how to include MOOCs on your resume here.

If you're still on the fence, luckily there is the option to take the class for absolutely free (sans certificate). To audit, simply click "Enroll for Free" and click "Audit" on the bottom of the second step. Voila, you're in!

This course is brand new, which is similar to the concept of generative AI itself. So instead of reviews (we'll come back and update), we've made a list of pros and cons based on our understanding of the course.

Pros and Cons of Generative AI for Software Engineering

Pros:

• Comprehensive Content: Each course builds seamlessly on the next, providing a clear learning path from beginner to advanced generative AI topics.
• Real-World Applications: The lessons emphasize practical use cases of generative AI, which helps in understanding how to apply this technology in everyday software development.
• Taught by Industry Experts: With contributions from Google Cloud and DeepLearning.AI, learners get the benefit of learning from AI leaders.
• Hands-On Projects: You get to work on real-life projects that provide practical experience using generative AI in software development.

Cons:

• Python Required: The focus on Python can be a limitation if you're more comfortable in other programming languages.
• Challenging for Beginners: While the course is "intermediate," beginners in AI may struggle without prior exposure to machine learning concepts.

Overall, the Udacity AI Product Manager Nanodegree program is well-regarded for its practical approach and strong support system, though it comes with some challenges, particularly related to cost and technical issues. For those who can navigate these challenges, it offers valuable skills and career support.

This course is great as a showable certification and jumping-off point, but may not teach you everything you need to know to get a role in a tech-adjacent field. Here are some other fabulous programs in the AI space, with a focus on hard skills to compliment the general knowledge provided in this cert:

If you're looking to know AI & Product Management: Duke University's AI Product Management

Both Duke and UVA are incredibly prestigious organizations working to increase public knowledge of product management. This is a mid-level course-- so have some basic knowledge under your belt first-- focused on product management in the realm of artificial intelligence. Read our full writeup here. It's also free to audit, but if you want the certificate (recommended), it's $79 a month to complete at your own pace.

If you're looking for ChatGPT basics: Prompt Engineering for ChatGPT

We don't usually write reviews for one-off classes, but we loved this one at Vanderbilt so much we made an exemption! Vanderbilt's Prompt Engineering for ChatGPT is a masterclass in all things Prompt Engineering. It's a beginner-level, bite-sized course that shows great on a resume. It's also super helpful for those looking to enhance their everyday lives with a little bit of artificial intelligence!

The course is taught by "top rated" professor Dr. Jules White, who boasts an impressive portfolio of five Coursera courses and more than 100,000 students. He's a Vanderbilt professor of Computer Science and has won a plethora of awards throughout the years. He also has a student-lead rating of 4.98/5. We love to see it.

Generative AI is revolutionizing software development, making this certification valuable for anyone looking to stand out in tech roles. Graduates of this course will gain a competitive edge in industries such as software engineering, AI research, and product development. It can also open doors to specialized AI roles in tech companies or startups exploring generative AI solutions.

The Generative AI for Software Development certificate offers a cutting-edge curriculum, perfect for those in software development looking to enhance their skills in generative AI. Its balance of theory and hands-on experience makes it a standout offering in the growing field of AI. If you're looking to stay at the forefront of software development, this course is a worthy investment.

Here at Bridged we are huge fans of stacking micro-certifications to achieve desired career results, which is why we created the skill tracker. We're still in beta and building a product to make your career planning fun and affordable. We'd love to talk to YOU! Was this article helpful? Did you enroll in the course?

Let us know at hello@getbridged.co