Andrew Ng’s impact in the field of AI education is significant, with a plethora of generative AI courses that cater to learners seeking to enter the AI job market.
The professor’s consistent launch of new generative AI courses has attracted attention, empowering individuals to pursue their desired AI careers. Notably, he founded an AI Fund of $175 million in 2018, underlining his commitment to the field.
DeepLearning.AI acknowledges Andrew Ng’s unparalleled influence in teaching the highest number of students globally, all outside of a traditional university setting.
Here is a list of 5 new courses announced by Andrew Ng:
Building Computer Vision Applications
Andrew Ng will livestream a new course teaching students how to build custom computer vision models on November 6th 10.30 pm IST.
The course covers crucial aspects, starting with the identification and scoping of vision applications. It explores technical feasibility, data quantity prerequisites, and selection of inputs and outputs for the vision model.
Participants will explore the selection of appropriate vision project types or models, be it Object Detection, Semantic Segmentation, Image Classification, or other suitable models.
Additionally, the course emphasises the application of Data-Centric AI, facilitating rapid iterative development through the systematic identification and resolution of data issues.
Finally, the program covers the process of deploying a Computer Vision model, guiding learners from initial model development to live deployment, ensuring a comprehensive understanding of the entire pipeline.
Generative AI for Everyone
Starting on November 2nd, Andrew Ng’s new Generative AI for everyone provides an insightful exploration of generative AI, offering an understanding of its functionalities and limitations.
Through hands-on exercises, participants learn practical applications for daily tasks and gain valuable insights into effective prompt engineering and advanced AI utilisation.
The curriculum delves into real-world applications, illustrating common use cases of generative AI. Participants have the opportunity to engage with generative AI tools, enabling the practical application of their knowledge. Moreover, the course offers a comprehensive understanding of AI’s influence on both business and societal landscapes.
By unpacking the impacts of generative AI on various sectors, the course equips learners with the tools to develop effective AI strategies and approaches, ensuring a well-rounded comprehension of AI’s application in real-world scenarios and its implications for both business and society.
Andrew Ng and LangChain
Andrew Ng launches a new generative AI course in collaboration with LangChain founder, Harrison Chase. The course, ‘Functions, Tools, and Agents with LangChain,’ focuses on updating developers about advanced LLMs and LangChain usage for working with models.
Ng highlights the recent course developments, emphasising function calling like OpenAI’s LLMs and handling structured data efficiently. The updated training algorithms now comprehend and output data like JSON, providing students direct hands-on experience.
The enhancements lead to more predictable and reliable LLMs, proficient in tool usage for complex problem-solving. The course also introduces LangChain Expression Language (LCEL) to simplify composing chains and agents.
ChatGPT Prompt Engineering for Developers
This course is in partnership with OpenAI. The ChatGPT Prompt Engineering for Developers, is taught using large language models (LLMs) to swiftly create robust applications.
The course by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) explains LLM functionality, prompt engineering best practices, and practical API application.
Students can explore tasks like summarising, inferring sentiment, text transformation, and automated content creation. Also principles for effective prompts, systematic prompt engineering, and building custom chatbots, demonstrated via various examples in our Jupyter notebook for direct hands-on experience are taught.
Deep Learning Specialisation
In Andrew Ng’s Deep Learning Specialisation course, students can expect to learn clear, concise modules facilitating self-paced learning. Practical techniques to initiate AI projects and craft an industry portfolio.
Foundational concepts explained through easy-to-understand lectures and interactive assignments. Content that remains up-to-date with the latest advancements in machine learning. Highly rated by over 120,000 learners with a score of 4.9 out of 5, making it one of the most favoured data science programs on Coursera. This is a longer course which is paced at 10 hours a week for three months.
Read More: 6 Brilliant New Free Courses by Andrew Ng on Generative AI
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