AI Agents and Agentic AI in Python: Powered by Generative AI Specialization

Colleagues, in the “AI Agents and Agentic AI in Python” training program you will build Autonomous AI Agents, create AI agents in Python that can operate independently, interact with APIs, and handle real-world tasks, master Core and Advanced Agent Concepts – Understand agent loops, tool integration, multi-agent collaboration, and design principles, and optimize AI Agents for Real-World Use – Develop resilient, efficient, and maintainable agents while balancing token costs, speed, and predictability. You will gain high-demand skills with Generative AI Agents, Business Logic, Agentic systems, Tool Calling, AI Security, Prompt Patterns, AI literacy, Artificial Intelligence, AI powered creativity, LLM Application, AI Enablement, Large Language Modeling, and File I/O. And use tools including OpenAI API, AI Workflows, AI Orchestration, ChatGPT, Prompt Engineering, Agentic Workflows, and Generative AI. Training lessons address: 1) AI Agents and Agentic AI with Python & Generative AI, 2Prompt Engineering for ChatGPT, and 3) AI Agents and Agentic AI Architecture in Python. 

Enroll today (teams & executives are welcome): https://imp.i384100.net/qWB7oy

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) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)

Advanced Learning Algorithms (DeepLearning.AI)

AI Colleagues,in the “Advanced Learning Algorithms” program from DeepLearning.AI you will build and train a neural network with TensorFlow to perform multi-class classification, apply best practices for machine learning development so that your models generalize to data and tasks in the real world, and use decision trees and tree ensemble methods, including random forests and boosted trees. You will gain highly marketaable skills including Applied Machine Learning, Machine Learning Algorithms, Supervised Learning, Deep Learning, Model Evaluation, Transfer Learning, Decision Tree Learning, Data Ethics, Model Training, Logistic Regression, Machine Learning, Model Optimization, Random Forest Algorithm, Fine-tuning, Responsible AI, and Artificial Neural Networks and useTensorflow, and Classification Algorithms. Training modules address: 1) Neural Networks, 2) Neural Networks Training, 3) Advice for Applying Machine Learning, and Decision Trees.

Enroll today (teams & executives are welcome): https://imp.i384100.net/3kzkVX 

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) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)

LLM Engineering That Works: Prompting, Tuning, and Retrieval Professional Certificate

AI Colleagues, the “LLM Engineering That Works: Prompting, Tuning, and Retrieval Professional Certificate”program combines 5 long courses, 19 short courses, and 4 add-on modules to cover the end-to-end lifecycle of large language models—from prompt design and model tuning to retrieval, evaluation, and deployment. You’ll learn to build robust, ethical, and cost-efficient LLM solutions through hands-on projects that mirror real-world workflows. By completing this program, you’ll gain the skills needed to design, implement, monitor, and improve scalable LLM-enabled applications across industries. You will: Learn prompting, tuning, retrieval, and scalable architectures for reliable AI applications. Design and deploy production-grade LLM systems combining prompting, tuning, and retrieval. Build reliable, scalable AI pipelines with evaluation, monitoring, and governance. And apply responsible AI practices, ethics, and safety throughout the lifecycle of LLMs. Gain high-demand skills in Responsible AI, Prompt Patterns, Model Optimization, Product Requirements, Feature Engineering, Model Training, Data Ethics, SQL, LLM Application, MLOps (Machine Learning Operations), Model Evaluation, and Systems Architecture. Training modules address: 1) Production AI Model Development and Ethics, 2) Building Reliable LLM Systems, 3) Testing and Refining LLM Applications, 4) Designing Production LLM Architectures, 5) Evaluating LLM Performance and Efficiency, and 6) Advancing Your Career in Production AI.

Enroll today (teams & executives are welcome): https://imp.i384100.net/5kx0no

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) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)

AI Agent Developer Specialization

Colleagues, in the “AI Agent Developer Specialization” program you will learn to design, build, and refine intelligent software agents using Python, generative AI, and agentic architectures for real-world applications. Build and deploy intelligent AI agents using Python, tools, memory, and reasoning, create custom GPTs and apply prompt engineering techniques for real-world tasks, and design trustworthy, responsible AI systems aligned with best practices. Gain high-demand skills involving Prompt Patterns, Generative AI Agents, Agentic systems, Retrieval-Augmented Generation (RAG), Data Presentation, AI powered creativity, LLM Application, Software Development, Document Management, Verification And Validation, Ideation, Responsible AI, and Data Visualization. You will also use tools including Agentic Workflows, Generative AI, ChatGPT, OpenAI API, Prompt Engineering, AI Workflows, and AI Orchestration. Skill-based training modules address: 1) AI Agents and Agentic AI with Python & Generative AI, 2) AI Agents and Agentic AI Architecture in Python, 3) OpenAI GPTs: Creating Your Own Custom AI Assistants, 4) Prompt Engineering for ChatGPT, 5) ChatGPT Advanced Data Analysis, and 6) Trustworthy Generative AI. 

Enroll today (teams & executives are welcome): https://imp.i384100.net/e1Bv4D 

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) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)

Unsupervised Learning, Recommenders, Reinforcement Learning (training)

Colleagues, in the “Unsupervised Learning, Recommenders, Reinforcement Learning” program you will learn to use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection, build recommender systems with a collaborative filtering approach and a content-based deep learning method, and develop a deep reinforcement learning model. Acquire high-demand skills in Anomaly Detection, Deep Learning, Supervised Learning, Artificial Intelligence, Dimensionality Reduction, Data Ethics, Unsupervised Learning, Applied Machine Learning, Reinforcement Learning, Artificial Neural Networks, Machine Learning, and Responsible AI. This program is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more). Unsupervised learning: Two key unsupervised learning algorithms: clustering and anomaly detection. Recommender systems: Making recommendations. Using per-item features. Collaborative filtering algorithm. Binary labels: favs. Mean normalization. TensorFlow implementation of collaborative filtering. Reinforcement learning: Learn about reinforcement learning, and build a deep Q-learning neural network in order to land a virtual lunar lander on Mars!

Enroll today (teams & executives are welcome): https://imp.i384100.net/xJb7g5

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) (Kindle)

Much career success, AI Academy (share with your team)

Machine Learning with Python: from Linear Models to Deep Learning (MITx)

Colleagues, the “Machine Learning with Python: from Linear Models to Deep Learning” program offers an in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. In this course, you will learn about principles and algorithms for turning training data into effective automated predictions, representation, over-fitting, regularization, generalization, VC dimension, clustering, classification, recommender problems, probabilistic modeling, reinforcement learning, and on-line algorithms, support vector machines, and neural networks/deep learning. Students will implement and experiment with the algorithms in several Python projects designed for different practical applications. Skill-based training modules include: 1) Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning, 2) Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models, 3) Choose suitable models for different applications, and 4) Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering.

Enroll today (teams and execs are welcome): https://edx.sjv.io/oNP9ao 

Recommended Reading:

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) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much success in your AI career, AI Academy (please subscribe and share with you colleagues)

Google AI Essentials (training)

Colleagues, the “Google AI Essentials” program is designed to help people across roles and industries get essential AI skills to boost their productivity, zero experience required. The course is taught by AI experts at Google who are working to make the technology helpful for everyone. In under 10 hours, they’ll do more than teach you about AI — they’ll show you how to actually use it in the real world. Stuck at the beginning of a project? You’ll learn how to use AI tools to generate ideas and content. Planning an event? You’ll use AI tools to help research, organize, and make more informed decisions. Drowning in a flooded inbox? You’ll use AI tools to help speed up those daily work tasks, like drafting email responses. You’ll also learn how to write effective prompts and use AI responsibly by identifying AI’s potential biases and avoiding harm. After you complete the course, you’ll earn a certificate from Google to share with your network and potential employers. By using AI as a helpful collaboration tool, you can set yourself up for success in today’s dynamic workplace — and you don’t even need programming skills to use it. Skill-based modules include: 1) Introduction to AI, 2) Maximize Productivity With AI Tools, 3) Discover the Art of Prompt Engineering, 4) Use AI Responsibly, and 5) Stay Ahead of the AI Curve. Learn generative AI tools to help develop ideas and content, make more informed decisions, and speed up daily work tasks. Write clear and specific prompts to get the output you want - you’ll apply prompting techniques to help summarize, create tag lines, and more. Use AI responsibly by identifying AI’s potential biases and avoiding harm. Develop strategies to stay up-to-date in the emerging landscape of AI. Gain high demand and highly marketable skills in Artificial Intelligence (AI), Prompt Engineering, Large Language Models (LLMs) and Generative AI.

Enroll today (teams & executives are welcome): https://imp.i384100.net/AgkRoa

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) (Kindle)

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

IBM Generative AI Engineering

During the “IBM Generative AI Engineering” program you will explore AI, generative AI, and prompt engineering, as well as data analysis, machine learning, and deep learning with Python. You'll gain hands-on experience with libraries like SciPy and scikit-learn, and develop applications using frameworks and models like BERT, GPT, and LLaMA. You'll also learn how to build LLM-based NLP applications using tools like Hugging Face Transformers, PyTorch, RAG, and LangChain, while diving deep into tokenization, language models, and transformer methods. Skill-based training modules include: 1) AI for Everyone: Master the Basics, 2) Introduction to Generative AI, 3) Introduction to Prompt Engineering, 4) Python Basics for Data Science, 5) Python for AI & Development Project, 6) Developing Generative AI Applications with Python, 7) Analyzing Data with Python, 8) PyTorch Basics for Machine Learning, 9) Deep Learning Fundamentals with Keras, 10) Generative AI: LLM Architecture & Data Preparation, 11) Model Foundations and NLP, 12) Language Models with Transformers, 13) Fine-Tuning Transformers, 14) Advanced Fine-Tuning for LLMs, 15) Agents with RAG and LangChain, and 16) RAG and LangChain App.

Enroll today (teams and execs are welcome): https://edx.sjv.io/QYzJOY 

Recommended Reading:

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) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much success in your AI career, AI Academy (please subscribe and share with you colleagues)

Optimizing Generative AI on Arm Processors: from Edge to Cloud

Colleagues, the “Optimizing Generative AI on Arm Processors: from Edge to Cloud” training shows you how to optimize GenAI workloads on real-world systems using techniques such as SIMD (SVE, Neon), low-bit quantization, and the optimized KleidiAI library. You will develop essential strategies and skills to build scalable, high-performance AI on edge and cloud-based platforms based on the most widespread processor architecture. You will learn how to optimize AI inference using Arm-specific techniques such as SIMD (SVE, Neon) and low-bit quantization. The course covers practical strategies for running generative AI efficiently on edge and cloud-based Arm platforms. You will also explore the trade-offs between cloud and edge deployment, gaining both theoretical knowledge and hands-on skills.

By the end of this course, you will have a strong foundation in deploying high-performance AI models on Arm hardware. Skill-based training modules include: 1) Challenges Facing Cloud and Edge GenAI Inference - Understanding the limitations and constraints of AI inference in different environments, 2) Generative AI Models - Exploring model architectures, training methodologies, and deployment considerations, 3) ML Frameworks and Optimized Libraries - A deep dive into AI software stacks, including PyTorch, llama.cpp, and Arm-specific optimizations, and 4) Optimization for CPU Inference - Techniques such as quantization, pruning, and leveraging SIMD instructions for faster AI performance.

Enroll today (teams and execs are welcome): https://edx.sjv.io/m4aaE1 

Recommended Reading:

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) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much success in your AI career, AI Academy (please subscribe and share with you colleagues)

The AI Sentinel (July 2026)

Colleagues, our goal is to provide AI professionals with up-to-date and actionable information to advance your career and income growth. “The global artificial intelligence market size is estimated to reach $3,497.26B by 2033, expanding at a CAGR of 30.6% from 2026 to 2033” as reported by Grand View Research. According to Ping.com the “AI engineer salary in 2026: $173K national median to $795K+ at OpenAI. Tier-by-tier AI compensation benchmarks, xAI wage data, and what TA leaders should do.” Major career growth awaits you.

Product Launches & Innovations: 

• Gemini 3.5 Flash - Google: A hyper-fast, agentic model that balances frontier intelligence with low latency. It is designed to handle long-horizon tasks, such as complex coding or financial document preparation, at a significantly reduced cost compared to previous flagship models.

• Gemini Enterprise for Customer Experience (CX) - Google: An agentic solution tailored for businesses to integrate shopping and customer service into a single interface. It includes prebuilt agents for food ordering and product discovery that connect directly to backend enterprise systems.

• AI for Good Global Summit Innovations (Geneva) - United Nations/AI for Good): A series of prototypes and robotic innovations showcased in early July 2026, including specialized robots like the Unitree G1 and the Aperobot, aimed at solving global agricultural and societal challenges.

• Claude Code (Opus 4.6 Updates) - Anthropic: Enhanced coding agent capabilities that leverage the Opus 4.6 model. It is designed for complex coding tasks that require advanced reasoning, multi-step planning, and long-form codebase management.

• Marble - World Labs: A "world model" capable of processing physical and spatial data to generate realistic simulations. This technology is being utilized for training autonomous systems, such as self-driving cars and robotics, by creating accurate virtual environments.

• Abridge Enterprise Clinical AI - Abridge: A scaling ambient AI platform that records patient-clinician conversations to automatically generate structured patient charts and medical records, significantly reducing administrative burnout in large health systems.

• Cerebras Wafer-Scale AI Chips - Cerebras: The latest generation of dinner-plate-sized AI chips, designed to eliminate the latency issues associated with routing data between smaller, separate GPUs. This hardware is increasingly supporting the massive throughput required for 2026's state-of-the-art agentic models.

Featured Resources:

• 10 Things That Matter in AI Right Now (MIT Technology Review - April 2026)

• AI in 2026: A Tale of Two AIs (Sequoia Capital - December 2025)

• How to Evaluate an AI SOC Platform in 2026: 6 Capabilities That Separate Leaders from Bolt-On AI solutions (The Hacker News - July 2026)

• Promoting Advanced Artificial Intelligence Innovation and Security  (The White House - June 2026)

• World Development Report 2026 - AI (World Bank - 2026)

Events:

• 4th World Conference on eXplainable Artificial Intelligence (XAI 2026 - Fortaleza, Brazil - July 1-3)

• AI Engineer World's Fair (AI Engineer Foundation - June 29–July 2, San Francisco, USA)

• Ai4 2026 (Ai4 - August 4–6, Las Vegas, USA)

• AMD Advancing AI 2026 (AMD - July 22-23, San Francisco, USA)

• ICML 2026 (International Conference on Machine Learning) (International Machine Learning Society  - July 6–11, Seoul, South Korea)

Career Development - Certification & Training Programs That Can Boost Your Income by 5%-10%:

• AI Foundations for Everyone Specialization (IBM)

• Apply Generative Adversarial Networks (GANs)

• AWS Certified AI Practitioner (AIF-C01)

• Data Structures, Algorithms, and Deep Learning Optimization

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

• Deep Learning Specialization

• Deep Learning with TensorFlow & PyTorch

• Deep Learning with Tensorflow, Keras and PyTorch 

• Deep Learning Specialization

• Deep Learning with PyTorch

• Generative AI for Cybersecurity

• Generative Deep Learning with TensorFlow

• IBM AI Developer Professional Certificate

• IBM AI Product Manager Professional Certificate

• Machine Learning Specialization

• Machine Vision, GANs, and Deep Reinforcement Learning

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

• Neural Networks and Deep Learning

• Structuring Deep Learning Projects

• TensorFlow Developer Professional Certificate

Enroll today (teams & execs are welcome).

Much success in your Artificial Intelligence career, AI Academy (share with colleagues & friends)