The Deep Learning Sentinel (August 2025)

Colleagues, our goal is to provide Deep Learning professionals with up-to-date and actionable information to advance your career and income growth.

Product Launches & Innovations 

• Allen Institute for AI's OMAI Project (August) 

• Apple On-Device and Server Foundation Language Models (July)

• DeepSeek R1 (March)

• Google Gemini 2.5 (March)

• Litmus7's 'Neural Intelligence' Hub (August) 

• OpenAI GPT-5 (August)

Featured Articles

• “AI and Machine Learning” (Harvard Business Review) 

• “Deep Learning” (Alan Turning Institute)

• “Deep Learning” (MIT Technology Review)

• “Deep Learning News & Articles” (IEEE Spectrum)

• “Features, Models, and Applications of Deep Learning in Music Composition” (American Journal of Information Science and Technology)

Featured Resources

• AWS Deep Learning

• DeepLearning.AI

• Google Vertex AI Platform

• MathWorks - Deep Learning

• nVidia Deep Learning Institute

Events

• AI & Big Data Expo Europe - September 24-25, 2025 (Amsterdam, Netherlands)

• AI Infra Summit - September 9-11, 2025 (Santa Clara, California, USA)

• Conference on Robot Learning (CoRL) - September 27-30, 2025 (Seoul, South Korea)

• Computer Science, Machine Learning and Big Data - September 14, 2025 (Bali, Indonesia)

• Meta Connect - September 17-18, 2025 (Online/Virtual)

• The AI Conference - September 17-18, 2025 (San Francisco, California, USA)

Career Development - Certs & Training

• Data Structures, Algorithms, and Deep Learning Optimization

• Deep Learning A-Z 2025: Neural Networks, AI & ChatGPT

• Deep Learning and Reinforcement Learning

• Deep Learning Specialization

• Deep Learning with TensorFlow & PyTorch

• Deep Learning with Tensorflow, Keras and PyTorch 

• Deep Learning Specialization

• Deep Learning with PyTorch

• Introduction to Deep Learning

• Machine Learning with Python: from Linear Models to Deep Learning

• Machine Learning A-Z: AI, Python & R

• Neural Networks and Deep Learning

• Structuring Deep Learning Projects

• TensorFlow Developer Professional Certificate

Enroll today (teams & execs are welcome). 

Much success in your DL career journey, Lawrence E. Wilson - AI Academy (share with colleagues & friends)

Generative AI for Everyone (training)

Colleagues, in the “Generative AI for Everyone” program you will learn what generative AI is and how it works, its common use cases, and what this technology can and cannot do, and How to think through the lifecycle of a generative AI project, from conception to launch, including how to build effective prompts. The potential opportunities and risks that generative AI technologies present to individuals, businesses, and society. Skills you'll gain - Generative AI Tools, Large Language Models, AI strategy, Generative AI and AI Productivity. Instructed by AI pioneer 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. You’ll get hands-on time with generative AI projects to put your knowledge into action and gain insight into its impact on both business and society. Skill-based lessons include: 1) Introduction to Generative AI - How Generative AI works, LLMs as a thought partner, AI is a general purpose technology, Writing, Reading, Chatting, What LLMs can and cannot do, Tips for prompting, Image generation, 2) Generative AI Projects - Using generative AI in software applications, Trying generative AI code yourself, Lifecycle of a generative AI project, Cost intuition, Retrieval Augmented Generation (RAG), Fine-tuning, Pre-training an LLM, Choosing a model, How LLMs follow instructions: Instruction tuning and RLHF, Tool use and agents, and 3) Generative AI in Business and Society - Day-to-day usage of web UI LLMs, Task analysis of jobs, Additional job analysis examples, New workflows and new opportunities, Teams to build generative AI software, Automation potential across sectors, Concerns about AI, Artificial General Intelligence, Responsible AI, and Building a more intelligent world.

Enroll today (teams & execs welcome): https://imp.i384100.net/9gKrZ4 

Download your free AI-ML-DL - Career Transformation Guide.

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Google Prompting Essentials Specialization

Colleagues, the “Google Prompting Essentials Specialization” program will enable you to practice using 5 steps to write effective prompts, apply prompting techniques to help you with every-day work tasks, use prompting to speed up data analysis and build presentations, and design prompts to create AI agents to role-play conversations and get expert feedback. Acquire highly marketable skills in Report Writing, Machine Learning, Document Management, Graphing, Human Centered Design, AI Personalization, Concision, Generative AI Agents, Data Visualization, Artificial Intelligence, Data Presentation, and Prompt Engineering. This four course program includes teaching modules: 1) Start Writing Prompts like a Pro, 2) Design Prompts for Everyday Work Tasks, 3) Speed Up Data Analysis and Presentation Building, and 4) Use AI as a Creative or Expert Partner. Through hands-on exercises and real-world examples, you’ll learn how to use AI to: Save time: Craft emails, brainstorm with ease, build tables and trackers, and summarize lengthy documents, Uncover and share powerful insights: Identify patterns in data, create compelling data visualizations, and even rehearse presentations., Tackle complex projects: Transform abstract ideas into actionable steps, use AI to role-play conversations, and get expert feedback, and Use AI responsibly: Evaluate your outputs for bias and errors, and iterate to get more helpful results. In the Applied Learning Project you will practice writing prompts for generative AI tools, developing practical skills you can apply right away. You'll use AI for idea generation, content creation, summarization, data analysis, and building AI agents.

Enroll today (teams & execs welcome): imp.i384100.net/bO1o6k 

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

3 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Retrieval Augmented Generation - RAG (training)

Colleagues, in the “Retrieval Augmented Generation” program from DeepLearning.AI you will learn to design and build RAG systems tailored to real-world needs, weigh tradeoffs between cost, speed, and quality to choose the right techniques for each component of a RAG system, and a foundational framework to adapt RAG systems as new tools and methods emerge. Gain high-demand skills in Secure Coding, Security Controls, Large Language Modeling, Information Management, Natural Language Processing, Sampling (Statistics), System Monitoring, Artificial Intelligence, Data Security, MLOps (Machine Learning Operations), Metadata Management, Application Performance Management, Prompt Engineering, Continuous Monitoring, Algorithms, and Generative AI. Learn how to build RAG systems that connect LLMs to external data sources. You’ll explore core components like retrievers, vector databases, and language models, and apply key techniques at both the component and system level. Through hands-on work with real production tools, you’ll gain the skills to design, refine, and evaluate reliable RAG pipelines - and adapt to new methods as the field advances. Skill-based training modules include: 1) RAG Overview, 2) Information Retrieval with Vector Databases, 3) LLMs and Text Generation, and 4) RAG Systems in Production. Through hands-on labs, you will: Build your first RAG system by writing retrieval and prompt augmentation functions and passing structured input into an LLM, Implement and compare retrieval methods like semantic search, BM25, and Reciprocal Rank Fusion to see how each impacts LLM responses, Scale your RAG system using Weaviate and a real news dataset—chunking, indexing, and retrieving documents with a vector database, Develop a domain-specific chatbot for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset, Improve chatbot reliability by handling real-world challenges like dynamic pricing and logging user interactions for monitoring and debugging, and Develop a domain-specific chatbot using open-source LLMs hosted by Together AI for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset.

Enroll today (teams & execs welcome): imp.i384100.net/550N6j 

For your listening-reading pleasure consider:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 -  “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

3 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Deep Learning with TensorFlow (training)

Colleagues, Deep Learning professionals earn on average $137,989+ per year according to ZipRecruiter. The Deep Learning with TensorFlow training program will equip you to build Deep Learning models in TensorFlow and Keras, interpret the results of Deep Learning models, troubleshoot and improve Deep Learning models, understand the language and fundamentals of artificial neural networks, and build your own Deep Learning projects. Skill-based training modules address: 1) Introduction to Deep Learning - artificial neural networks, and the breadth of transformative applications it produces. Jon also goes over how to run the code examples provided throughout the LiveLessons, and then he builds an introductory neural network with you, 2) How Deep Learning Works - main families of deep neural networks and their applications. The heart of the lesson is a high-level overview of the essential theory that underlies deep learning. To bring this theory to life, Jon shows you deep learning in action via a web application called the TensorFlow Playground, archetypal deep learning datasets, and then you build a deep neural network together to tackle a classic machine vision problem, 3) Convolutional Networks - convolutional layers and how they have can be stacked to solve increasingly complex problems with larger data sets. In order to make sense of the outputs from these sophisticated models, the TensorBoard result-visualization tool is added to your arsenal at the end of the lesson, 4) Introduction to TensFlow - high-level deep learning API Keras to build your models. In this lesson, the leading Deep Learning libraries are compared, and then you get down to business with TensorFlow, the open-source library doing the heavy neural network-lifting underneath Keras and, in Jon’s opinion, clearly the best choice from the options available. Given this, the second half of the lesson is dedicated to building your own deep learning models in TensorFlow, and 5) Improving Deep Networks - performance of your deep learning models, including by tuning model hyperparameters. The lesson concludes by discussing how to build your own deep learning project as well as outlining resources for further self-study.

Enroll today (teams & execs welcome): https://tinyurl.com/y6vek5nz 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (subscribe & share)