Go beyond the traditional degrees: kick start your AI education with Free online courses
Deeplearning.ai is a treasure dungeon with accessible and flexible learning opportunities - learn how to transform new knowledge into Real-World skills and job chances.
The world is moving too fast! Fast information, news, technology advancement.
People also talk to fast: it looks like no one wants to miss a second to make a point, shut up the others, and overall without listening.
Certainly we must improve our soft skills: AI is becoming better and better at mimicking our skills, doing all of them faster and with high accuracy. But we need to also to start learning more about Generative AI: the mechanisms, the way to use it, the limits and the strengths.
Learning in 2024
In the last years acquiring new skills has never been more accessible than it is now with the rise of technology. The availability of vast amounts of information through the internet has opened doors to endless opportunities, especially when it comes to education.
Among these resources, free online courses have gained immense popularity due to their convenience, flexibility, and affordability. However, while numerous options exist, not all free courses offer top-notch quality that can translate into practical application. In this newsletter I will present you a high reward dungeon, full of treasures: a place where you can learn effectively using free courses offered by Deeplearning.ai, founded by renowned AI expert, Andrew Ng.
An outdated myth
First thing first, let us address the elephant in the room - why choose free courses over traditional university programs?
For starters, financial constraints often prevent individuals from pursuing higher education, forcing them to put off their dreams until they can manage the tuition fees. It is not the same in all the Countries, but the truth is that high education is expensive (time, material, living expenses…).
Free courses make education accessible to everyone regardless of their economic background, which presents an excellent opportunity for those who may not be able to afford formal degrees. Moreover, most free courses are self-paced, allowing every kind of students to work around their schedules instead of adhering to strict timetables set by universities. This unparalleled freedom and flexibility makes it easier even for working professionals to upskill themselves without disrupting their careers.
I took My first online certification in 2013 on Alison.com: and after that I changed my career path and became an Industrial Process Control Automation engineer.
Without knowledge action is useless and knowledge without action is futile.
We must never forget this: learning does not only entail absorbing theoretical concepts; it also involves applying them in practice. Merely watching video lectures and taking quizzes is not enough!
In schools students must complete projects to solidify their understanding of the subject matter. In a similar way when modern learners complete assignments independently we can really say that a skill has been acquired. Learning today means: put your skills in real-world scenarios, enhance your critical thinking abilities and encourage new problem-solving skills.
In this regard, Deeplearning.ai offers various hands-on exercises and coding challenges throughout its courses, equipping students with practical experience that can directly apply to industry needs. Andrew Ng is posting new courses announcements every week: and all of them are emergent topics from the Generative AI community and breakthroughs.
DeepLearning.AI
Let’s dive deeper into Deeplearning.ai. Launched in 2017 by Stanford University professor Andrew Ng, Deeplearning.ai delivers cutting-edge content.
The platform covers topics like neural networks, reinforcement learning, and computer vision.
Andrew Ng is widely recognized as a pioneer in the field of artificial intelligence (AI) and machine learning (ML). He co-founded Coursera and served as Baidu’s Vice President and Chief Scientist before launching Deeplearning.ai. His extensive expertise and reputation lend credibility to his platform, attracting top-tier talent from across the globe.
You can register for FREE and check out the catalog of courses
Deeplearning.ai offers a diverse range of courses catering to different levels of proficiency. Check them out here and pick your starting point: personally I started months ago with Generative AI for everyone and Prompt Engineering with Llama 2 & 3 (in reality at the time I attended the courses it was only about Llama2… Llama3 was not out yet 😅) .
Generative AI for everyone
Instructed directly by Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI. Andrew will guide you through how generative AI works and what it can (and can’t) do. It includes hands-on exercises where you’ll learn to use generative AI to help in day-to-day work and receive tips on effective prompt engineering, as well as learning how to go beyond prompting for more advanced uses of AI.
You’ll delve into real-world applications and learn common use cases, and get hands-on time with generative AI tools to put your knowledge into action, and gain insight into AI’s impact on both business and society.
This course was created to ensure everyone can be a participant in our AI-powered future.
Prompt Engineering with Llama 2 & 3
Open up your prompt engineering to the Llama 2 & 3 collection of models! Learn best practices for prompting and building applications with these powerful open commercial license models.
Interact with the Llama 2 and Llama 3 models with a simple API call, and explore the differences in output between models for a variety of tasks.
What you’ll do:
Learn best practices for prompting and selecting among the Llama 2 & 3 models by using them as a personal assistant to help you complete day-to-day tasks.
Experiment with advanced prompt engineering techniques, like few-shot prompting to get Llama 2 to classify the sentiment of text messages, and chain-of-thought prompting to solve logic problems.
Treat Code Llama as a pair programming partner to both learn to write and improve code.
Promote safe and responsible use of LLMs by having Llama Guard check user prompts and model responses for harmful content.
Llama 2 and Llama 3 models and model weights are free to download, including quantized model versions that can run on your local machine. Join a thriving community of open source developers that is building applications powered by Llama 2 and Llama 3.
Open Source Models with Hugging Face.
In this course, you’ll learn how to find and filter open source models on Hugging Face Hub to perform text, audio, image, and multimodal tasks using the Hugging Face transformers library. You’ll also learn to easily share your AI apps with a user-friendly interface or via API and run them locally and on the cloud using Gradio and Hugging Face Spaces.
What you'll do in this course:
Use the transformers library to turn a small language model into a chatbot capable of multi-turn conversations to answer follow-up questions.
Translate between languages, summarize documents, and measure the similarity between two pieces of text, which can be used for search and retrieval.
Convert audio to text with Automatic Speech Recognition (ASR), and convert text to audio using Text to Speech (TTS).
Perform zero-shot audio classification, to classify audio without fine-tuning the model.
Generate an audio narration describing an image by combining object detection and text-to-speech models.
Identify objects or regions in an image by prompting a zero-shot image segmentation model with points to identify the object that you want to select.
The course will provide you with the building blocks that you can combine into a pipeline to build your AI-enabled applications!
AI Agents in LangGraph
LangChain, a popular open source framework for building LLM applications, recently introduced LangGraph. This extension allows developers to create highly controllable agents.
In AI Agents in LangGraph you will learn to build an agent from scratch using Python and an LLM, and then rebuild it using LangGraph to learn its components and how to combine them to build flow-based applications.
Additionally, you will learn about agentic search, which returns multiple answers in an agent-friendly format, enhancing the agent’s built-in knowledge. This course will show you how to use agentic search in your applications to provide better data for agents to enhance their output.
Function-Calling and Data Extraction with LLMs
This course will teach you two critical skills for building applications with LLMs: function-calling and structured data extraction.
Function-calling allows you to extend LLMs with custom capabilities by enabling them to form calls to external functions based on natural language instructions. Structured data extraction enables LLMs to pull usable information from unstructured text.
In Function-Calling and Data Extraction with LLMs you’ll work with NexusRavenV2-13B, an open source model fine-tuned for function-calling and data extraction. Quoting the announcement:
The model, freely available on Hugging Face, outperforms GPT-4 in some function-calling tasks, and has 13 billion parameters so it can be hosted locally.
⚠️ The claim is a little bit too much: I mean, to run a 13B model locally you need quite a decent GPU, with at least 8GB of VRAM… If you have it no problems!
Conclusions
I have no affiliation with DeepLearning.AI, and I am not being sponsored by them: the only connection is that I am an active learner on their amazing platform. Every Course allows you to access Generative AI models, and test them out first hand.
One of the notable features of Deeplearning.ai is its emphasis on community building through discussion boards, Slack groups, and Facebook communities. These virtual spaces allow students to interact with peers globally, ask questions, share insights, and provide support to each other, creating a helpful learning environment that transcends borders.
Deeplearning.ai frequently hosts webinars featuring prominent speakers in the field, sharing their experiences and offering insights into current trends. These events present valuable networking opportunities for participants and expose them to potential career prospects.
Lastly, another significant advantage of DeeplearningAI's courses is the certificate awarded upon completion. While certificates do not hold the same value as academic qualifications, they serve as evidence of skill acquisition, and to show off (believe me, it works) to prospective employers that we possess relevant competencies.
It may lead you to better job placement or promotion!
So… what are you waiting for?
The future of AGI is uncertain: AI has many skills, but is that intelligence? And we are the only ones who can do something about it. This article is my gift for the week!
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This is only the start!
Hope you will find all of this useful. Feel free to contact me on Medium.
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