#deeplearning.ai prompt engineering

[mr-entj]

Hello Mr. ENTJ. I'm an ENTJ sp/so 3 woman in her early twenties with a similar story to yours (Asian immigrant with a chip on her shoulder, used going to university as a way to break generational cycles). I graduated last month and have managed to break into strategy consulting with a firm that specialises in AI. Given your insider view into AI and your experience also starting out as a consultant, I would love to hear about any insights you might have or advice you may have for someone in my position. I would also be happy to take this discussion to somewhere like Discord if you'd prefer not to share in public/would like more context on my situation. Thank you!

Insights for your career or insights on AI in general?

On management consulting as a career, check the #management consulting tag.

On being a consultant working in AI:

Develop a solid understanding of the technical foundation behind LLMs. You don’t need a computer science degree, but you should know how they’re built and what they can do. Without this knowledge, you won’t be able to apply them effectively to solve any real-world problems. A great starting point is deeplearning.ai by Andrew Ng: Fundamentals, Prompt Engineering, Fine Tuning

Know all the terminology and definitions. What's fine tuning? What's prompt engineering? What's a hallucination? Why do they happen? Here's a good starter guide.

Understand the difference between various models, not just in capabilities but also training, pricing, and usage trends. Great sources include Artificial Analysis and Hugging Face.

Keep up to date on the newest and hottest AI startups. Some are hype trash milking the AI gravy train but others have actual use cases. This will reveal unique and interesting use cases in addition to emerging capabilities. Example: Forbes List.

On the industry of AI:

It's here to stay. You can't put the genie back in the bottle (for anyone reading this who's still a skeptic).

AI will eliminate certain jobs that are easily automated (ex: quality assurance engineers) but also create new ones or make existing ones more important and in-demand (ex: prompt engineers, machine learning engineers, etc.)

The most valuable career paths will be the ones that deal with human interaction, connection, and communication. Soft skills are more important than ever because technical tasks can be offloaded to AI. As Sam Altman once told me in a meeting: "English is the new coding language."

Open source models will win (Llama, Mistral, Deep Seek) because closed source models don't have a moat. Pick the cheapest model because they're all similarly capable.

The money is in the compute, not the models -- AI chips, AI infrastructure, etc. are a scarce resource and the new oil. This is why OpenAI ($150 billion valuation) is only 5% the value of NVIDIA (a $3 trillion dollar behemoth). Follow the compute because this is where the growth will happen.

America and China will lead in the rapid development and deployment of AI technology; the EU will lead in regulation. Keep your eye on these 3 regions depending on what you're looking to better understand.

[trendsnova]

5 Essential AI Courses to Take in 2025 — No Matter Your Industry

Your fastest path to mastering AI skills that top companies are hiring for

AI Isn't Optional Anymore — It's the New Literacy

If there's one capability that will determine achievement in 2025 and beyond, it's artificial intelligence. No longer the exclusive province of Silicon Valley engineers, AI is now part of the everyday arsenal in marketing, education, finance, design, and healthcare.

A recent report from McKinsey estimates AI has the potential to inject more than $13 trillion into the economy by 2030. That's not a niche—it's a revolution. And those who know how to tap it will have a huge career advantage.

The best part? You don't require a computer science degree to get started. Nowadays, top AI education is a click away. The next five courses are some of the most prestigious and useful available, supported by giants like Google, Stanford, and DeepLearning.AI.

Google AI Essentials (Coursera) Best For: Complete beginners looking for a reliable, hands-on primer Google AI Essentials aims to equip you with a solid understanding of how AI works and how to apply it in your role, even if tech is not your background. It touches on practical uses of AI and even includes exercises to create your first AI-powered tools with Google's suite.

With a Google and Coursera certificate, this course is unique on a résumé and enables professionals to begin applying AI quickly in content writing, admin tasks, or data analysis.

AI For Everyone by Andrew Ng (Coursera) Best For: Entrepreneurs, managers, and non-technical teams Teased out by Coursera co-founder and former Google Brain boss Andrew Ng, a legendary in the field, the course is not about code but strategy for AI—how to think about the role of AI in business and society.

It’s perfect for decision-makers who want to speak the language of AI without writing a single line of code. You’ll learn how to identify which problems AI can solve, and how to build teams around those solutions.

Machine Learning Specialization (Stanford + DeepLearning.AI) Best For: Learners who want depth, and a Stanford-backed certificate If you're willing to dive deeper, this three-course specialisation—again taught by Andrew Ng—teaches the principles of supervised learning, unsupervised learning, and ML engineering best practices.

This is one of the best-known ML programmes in the world and provides you with a solid grounding to transition into AI work or create your own projects. It's an essential if you're keen on the technical aspects.

Prompt Engineering for ChatGPT (DeepLearning.AI + OpenAI) Best For: Creators, marketers, copywriters, and researchers Prompt engineering is rapidly turning into the most sought-after AI skill. In this course, you learn how to effectively interact with large language models such as ChatGPT so you can obtain the most accurate and creative output.

You will discover how to frame prompts for various purposes—summarizing, content writing, programming assistance, and more. Whether you are writing articles, emails, code, or strategies, prompt mastery is a productivity shortcut to 10x.

AI Product Management (Duke University on Coursera) Ideal For: Future product managers and startup entrepreneurs AI isn't merely about creating tools—it's about creating the right tools. This Duke University course is designed to get you to market with AI-powered products.

You'll learn to design, test, and release AI systems with consideration for user requirements, data ethics, and risk. With case studies and frameworks from leading product leaders, it's ideal for professionals who want to drive AI innovation in their firm or startup.

Why These Courses Matter These aren't random YouTube tutorials. Each one is instructed by Stanford, Google, OpenAI, or top university experts. More significantly, they provide you with practical know-how that's applicable in almost every profession.

If you are a writer wanting to apply AI for quicker content generation or a manager seeking to revolutionize your company's process, these courses will make you AI-literate—quickly.

Final Thought AI is not just a passing trend—it’s the skill that will define career trajectories for the next decade. The sooner you get started, the further ahead you’ll be when everyone else starts catching up.

Choose one course today, block 30 minutes on your calendar, and start your journey. You’ll thank yourself in six months.

[nikhilvaidyahrc]

Top 5 AI Certifications That Are Actually Worth It in 2025

Published by Prism HRC – Leading IT Recruitment Agency in Mumbai

Let’s face it, in 2025, AI is not "nice to know." It’s everywhere. From chatbots and content marketing to finance and medicine, artificial intelligence is the force working behind the scenes. That also means employers are actively searching for professionals who understand AI or at least know how to work alongside it.

But with countless online courses out there, it’s tough to know which certifications actually carry weight. Which ones make your resume stand out to real hiring managers and recruiters?

We’ve curated the top five AI certifications that are genuinely worth your time, effort, and investment in 2025, whether you’re a fresher, a seasoned techie, or someone switching careers.

Google Professional Machine Learning Engineer

Why it’s worth it: This certification shows that you can design, develop, and deploy machine learning models on Google Cloud. It’s widely respected in the industry, especially if you’re eyeing cloud-based AI roles.

Who it’s for: Mid-level professionals, data scientists, ML engineers

What you'll learn:

Defining machine learning problems

Feature engineering

Model architecture and deployment

Tools like Vertex AI, BigQuery, and TensorFlow

Bonus tip: Just having Google’s name on your resume adds major credibility, especially if you're applying to MNCs or product companies.

IBM Applied AI Professional Certificate (via Coursera)

Why it’s worth it: This course is one of the most beginner-friendly yet hands-on AI certifications out there. It teaches you practical tools and includes real-world projects you can add to your portfolio.

Who it’s for: Freshers, career changers, and even non-programmers curious about AI

What you'll learn:

Foundations of AI

Python programming for AI

IBM Watson tools and services

How to build chatbots and deploy AI applications

Pro tip: The included labs and projects are great for showcasing your work on LinkedIn or GitHub.

Microsoft Certified: Azure AI Fundamentals

Why it’s worth it: A solid starting point for anyone looking to understand AI through the lens of Microsoft’s Azure platform. This course makes complex AI ideas approachable without diving into deep code.

Who it’s for: Newcomers, business analysts, marketers, and non-tech professionals exploring a switch to AI

What you'll learn:

Core machine learning and AI principles

Natural language processing, computer vision

Responsible AI practices

Use cases and tools in Azure

Why it stands out: If you’re applying to companies already using Microsoft tools, this certification puts you ahead of the pack.

Stanford Online: Machine Learning Specialization by Andrew Ng (on Coursera)

Why it’s worth it: Andrew Ng is a well-known name in the AI world, and his course has helped millions break into machine learning. The 2025 version is updated, relevant, and perfect for serious learners who want a deep understanding.

Who it’s for: Developers, tech enthusiasts, aspiring machine learning engineers

What you’ll learn:

Supervised learning and neural networks

Bias-variance tradeoff

Decision trees

Model evaluation and tuning

What makes it special: This isn’t just a theory-heavy course. It helps you understand how machine learning actually works, and that knowledge is rare and respected.

DeepLearning.AI’s Generative AI with LLMs Specialization

Why it’s worth it: Let’s be honest, generative AI is everywhere right now. Whether you’re playing with ChatGPT or building AI tools at work, this course puts you in sync with the future.

Who it’s for: Developers, content creators, product managers, and tech professionals working with AI APIs

What you’ll learn:

Prompt engineering strategies

How large language models function

Fine-tuning LLMs

Building ethically sound GenAI applications

Hot tip: If you're interviewing for product, content, or R&D roles related to AI, this certification will make you stand out.

Before you go

Let’s cut through the noise. There are tons of AI courses out there, but only a few actually help you grow. These five certifications offer real skills, portfolio projects, and recruiter-approved credibility.

If you’re planning to enter AI, grow in your current role, or shift from another domain, one of these certifications could be the best decision you make in 2025.

Still unsure which AI path is right for your career?

Prism HRC can help you make the smart move. We match skilled talent with companies hiring in AI, data, and cloud, and we know exactly what certifications employers are asking for right now.

Based in Gorai-2, Borivali West, Mumbai Website: www.prismhrc.com Instagram: @jobssimplified LinkedIn: Prism HRC

[aishwaryaanair]

Breaking Into the AI Code: Essential Certifications for Tech Enthusiasts

Artificial Intelligence (AI) has swiftly transitioned from a futuristic concept to an integral part of our daily lives. From voice-activated assistants to predictive analytics and self-driving cars, AI powers countless innovations, making it one of the most sought-after skills in today’s job market. For tech enthusiasts looking to dive deep into this transformative technology, the right certifications can open doors to lucrative opportunities and exciting challenges.

Why AI Certifications Are Crucial for Tech Enthusiasts

AI is a rapidly evolving field, and staying updated requires continuous learning. Certifications offer:

Structured Learning Paths: They provide a systematic approach to mastering AI concepts and tools.

Industry-Relevant Skills: Certifications align with current industry needs, focusing on practical applications.

Validation of Expertise: Earning a certification demonstrates your commitment and skills to potential employers.

Networking Opportunities: Many programs connect learners with industry leaders and peers.

Whether you’re a programmer, a data analyst, or a budding tech enthusiast, an AI certification is a stepping stone to achieving your professional goals.

AI+ Prompt Engineer™ by AI Certs

The AI+ Prompt Engineer™ certification by AI Certs is a game-changer for anyone fascinated by the intersection of language and technology. This course focuses on crafting effective prompts for AI systems, a critical skill as conversational AI tools like ChatGPT gain prominence.

Key Features:

Comprehensive Curriculum: Covers the art and science of prompt engineering, optimization techniques, and applications across industries.

Hands-On Training: Learners engage in real-world projects to create and refine prompts for various AI models.

Industry Insights: Understand how prompt engineering drives innovations in customer service, marketing, and product development.

For tech enthusiasts eager to make an impact in AI-driven communication and automation, this certification is a must-have.

Use the coupon code NEWCOURSE25 to get 25% OFF on AI CERTS’ certifications. Don’t miss out on this limited-time offer! Visit this link to explore the courses and enroll today.

Machine Learning Certification by Stanford University (Coursera)

Stanford’s renowned Machine Learning Certification by Professor Andrew Ng is a favorite among AI enthusiasts. This beginner-friendly course covers foundational topics in machine learning, including supervised and unsupervised learning, neural networks, and data analysis.

Why Choose This Course?

Offers a solid introduction to AI concepts.

Provides practical assignments to apply your knowledge.

Delivered by one of the world’s leading AI educators.

Deep Learning Specialization by DeepLearning.AI (Coursera)

For tech enthusiasts eager to specialize in deep learning, the Deep Learning Specialization is a fantastic choice. This program, also led by Andrew Ng, dives into neural networks, natural language processing (NLP), and computer vision.

Key Highlights:

Build, train, and optimize deep neural networks.

Explore advanced AI applications like image recognition and sequence models.

Learn through interactive assignments and project.

How to Choose the Right AI Certification

With so many certifications available, choosing the right one can feel overwhelming. Here’s a simple guide to help you decide:

Assess Your Goals: Are you interested in programming, data science, or application development? Select a certification that aligns with your career aspirations.

Skill Level: Beginners should opt for foundational courses like Stanford’s Machine Learning Certification, while advanced learners might explore deep learning or robotics programs.

Practical Experience: Hands-on projects are essential for building confidence and showcasing your skills to employers.

Industry Recognition: Certifications from reputed institutions like AI Certs, Stanford, or DeepLearning.AI carry significant weight in the job market.

The Future of AI Careers for Tech Enthusiasts

The demand for AI expertise spans across industries. From healthcare and finance to gaming and education, professionals with AI skills are shaping the future. Here’s why now is the perfect time to invest in AI certifications:

High Demand: The global AI market is projected to reach $190 billion by 2025, creating millions of jobs.

Lucrative Salaries: AI professionals command competitive salaries, often exceeding six figures.

Innovation Opportunities: AI certifications equip you to solve complex problems and drive innovation.

A Roadmap to AI Success

Breaking into AI as a tech enthusiast doesn’t have to be daunting. With beginner-friendly certifications like AI+ Prompt Engineer™ or advanced programs like Deep Learning Specialization, you can tailor your learning journey to suit your interests and goals.

Take the First Step Today

AI is not just the future — it’s the present. With the right certification, you can transform your passion for technology into a thriving career. Whether you’re crafting innovative prompts, designing intelligent robots, or mastering neural networks, the opportunities are endless.

[carolchung-eng]

Dr. Strangelove (How I learned to stop worrying and love GenAI)

OK, I tried to ignore GenAI (generative AI) because I feared the consequences of its existence (becoming obsolete or lesser valued as a software engineer or putting non-engineers out of work). But I finally decided AI is not going away so I might as well understand what it is good for. This is a high level post about my initial observations with ChatGPT (v3.5) and Large Language Models (LLMs) in general.

ChatGPT is amazing with language (Natural Language Processing - NLP). I've been testing it on a variety of tasks where the most complex was a request to organize unstructured text into a specific database table. The results were mixed (many of the terms which I wanted to parse were domain-specific and the model had not been trained in that domain). However, it can do simple text parsing (like identify book title and author pairs in a long string of text that includes information that is non-book related) much better than I would expect (even when the input data format does not follow a specific pattern).

ChatGPT v3.5 is not capable of multi-modal input/output. When I requested a rap beat in a prompt, the response was that it could not produce audio (although this is an expected feature in v4). It did produce a rather entertaining rap for me (in text), which I was rather surprised by. In future versions of GenAI (which could include other LLMs), I am excited for interacting with AI via speech and getting text output (or vice versa or other media formats).

Efficiency - When working with an LLM, I think an initial challenge will be to find the most efficient model that will help you accomplish the task at hand. My first thought is that a smaller model might be more cost-effective in terms of running tasks against the model and doing things like fine-tuning and/or pre-training the model if those are necessary.

Efficiency2 - Another cost consideration will be where the LLM is hosted. In one course I am taking, the course is partnered with AWS as a potential host. But it seems like LLM hosting/infrastructure will be a competitive space for the future.

Potential uses for software engineers (code documentation and testing software). When I did testing with GitHub copilot, I saw that when I wrote comments before writing a function, the predictions for the function logic were pretty good. When I put prompts into ChatGPT about whether it was able to write documentation for functions, it responded that this was a capability. I didn't test this out but it seems logical. For proprietary software, using an LLM for internal documentation would just require hosting the LLM privately (I believe). I'm also a bit curious about how an LLM might be used to write automated tests (or to update existing automated tests based on small/medium code changes). When I asked ChatGPT about its capabilities around unit tests and integration tests, it responded positively but I did not test this extensively. So I do not know how specific or high level its test responses would be.

I was so surprised at how well ChatGPT understands language that I started to instinctively refer to it as "you" within the prompts and it understood the "you" as referencing itself. This is a strange existence but I think that LLMs can be seen as tools to handle some of the tedious or lower priority work that are "nice to have" or time-consuming.

Resources:

ChatGPT

Generative AI with Large Language Models (Coursera by DeepLearning.AI, AWS)

[librarianship020]

Here are the top 15 free courses recommend to learn AI

Microsoft, Google, Harvard University, DeepLearning.AI, LinkedIn, Massachusetts Institute of Technology (MIT) and Stanford University have all released free courses on AI 👨‍🎓 Here are the top 15 free courses I’d recommend to learn AI in 2023: Foundations of Prompt Engineering This course introduces the basics of prompt engineering and progresses to advanced prompt techniques. ✔…

[sergey-tihon]

F# Weekly #33, 2023 – SponsorLink & Rider F# features

Welcome to F# Weekly, A roundup of F# content from this past week: News SponsorLink: trying something new-ish for OSS sustainability (cazzulino.com) Six Labors : Announcing ImageSharp.Drawing 1.0.0 Large Language Models with Semantic Search – DeepLearning.AI Prompt engineering tips – Surface Duo Blog (microsoft.com) Multi-Branch Graph Available for General Audiences – Visual Studio Blog…

[ericvanderburg]

OpenAI offers users a free prompt engineering course in collaboration with DeepLearning.AI

http://i.securitythinkingcap.com/Sp6jvv

[tecnobinaria]

ChatGPT Prompt Engineering para desarrolladores : Curso Gratis! (En Inglés)

ChatGPT Prompt Engineering para desarrolladores : Curso Gratis! (En Inglés)

OpenAI y DeepLearning.AI han lanzado un curso titulado ChatGPT Prompt Engineering for Developers. En el básicamente te enseñaran a mejorar en la creación de Prompts (Indicaciones) para usar en el desarrollo con Inteligencias Artificiales como ChatGPT. What you’ll learn in this course In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly…