Generative Adversarial Networks (GANs) Specialization

Colleagues, rooted in game theory, GANs have wide-spread application: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, and turning 2D images to 3D. In the “Generative Adversarial Networks (GANs) Specialization” you will: Understand GAN components, build basic GANs using PyTorch and advanced DCGANs using convolutional layers, control your GAN and build conditional GAN. Compare generative models, use FID method to assess GAN fidelity and diversity, learn to detect bias in GAN, and implement StyleGAN techniques. Use GANs for data augmentation and privacy preservation, survey GANs applications. Examine and build Pix2Pix and CycleGAN for image translation. And you will acquire highly marketable skills with Data Synthesis, Machine Learning, Model Evaluation, Image Analysis, Responsible AI, Deep Learning, Convolutional Neural Networks, Image Quality, Data Ethic, Generative Model Architecture, Information Privacy, and Model Training. Tools you will learn cover: PyTorch (Machine Learning Library), Generative AI, and Generative Adversarial Networks (GANs). Skill-based lessons include: 1) Build Basic Generative Adversarial Networks (GANs), 2) Build Better Generative Adversarial Networks (GANs), and 3) Apply Generative Adversarial Networks (GANs).

Enroll today (teams & executives are welcome): https://imp.i384100.net/Jk4G4N

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) (Kindle)

3 - The Race for Quantum Computing (Audible) (Kindle) 

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

Prompt Design, Grounding, and RAG with Vertex AI Specialization

Colleagues, in the “Prompt Design, Grounding, and RAG with Vertex AI Specialization” begin with generative AI and large language model fundamentals, then explore prompt engineering and Vertex AI Studio. As you progress, you’ll work with text and multimodal embeddings, grounding techniques, controlled generation, and multimodal Gemini use cases. You’ll then apply these concepts to semantic search, hybrid search, multimodal RAG, and LLM-powered application architectures. Build Grounded Generative AI Applications. Design prompts, ground Gemini responses, and build RAG applications with Vertex AI. You will learn to: Design effective prompts for Gemini and Vertex AI using prompt patterns, configurations, and tuning techniques. Build grounded RAG workflows with embeddings, vector search, and your own documents or multimodal data. Create generative AI applications that combine Gemini, multimodal inputs, semantic search, and hybrid retrieval. And you will gain hands-on experience with Metadata Management, Embeddings, Prompt Patterns, Data Stores, Generative AI Agents, Google Cloud Platform, AI Literacy, Large Language Modeling, Retrieval-Augmented Generation, Artificial Intelligence, LLM Application, Image Analysis, Multimodal Prompts, Prompt Engineering Tools, and Generative Model Architectures. And acquire knowledge of high-demand tools including Google Gemini, Prompt Engineering, Generative AI, Vector Databases, and Gemini. Training lessons cover: 1) Generative AI, 2) Large Language Models, 3) Vertex AI Studio, 4) Generative AI with Vertex AI: Prompt Design, 5) Grounding Gemini Models in Vertex AI, 6) Create Generative AI Apps on Google Cloud, 7) Multimodal Use Cases with Gemini, 8) Vertex AI Embeddings: Text and Multimodal, 9) Vector Search and Embeddings, and 10) Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API. 

Enroll today (teams & executives are welcome): https://imp.i384100.net/ZV3W6X

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)

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

Much career success, AI Academy (kindly subscribe and share with your peers)

Microsoft Agentic AI Business Solutions Architect (Exam AB-100)

AI Colleagues, the “Microsoft Agentic AI Business Solutions Architect (Exam AB-100)” program is designed to empower professionals with the latest knowledge and practical skills required to excel in the rapidly evolving world of AI-driven business solutions. Organizations are increasingly relying on advanced AI technologies to drive innovation and maintain a competitive edge. The demand for experts who can design, architect, implement, and manage agentic AI solutions has never been greater. This course provides an in-depth exploration of agentic AI concepts, frameworks, and best practices, ensuring learners are well-prepared for certification and real-world challenges. You will learn to: Plan AI-powered business solutions by analyzing requirements and defining clear objectives, Design an effective overall AI strategy tailored to business needs and goals, Evaluate the costs and benefits associated with implementing AI-powered business solutions, Develop AI-powered business solutions by designing AI agents and identifying opportunities for solution extensibility, Orchestrate and configure prebuilt AI agents and applications to support business processes, Deploy and manage AI-powered business solutions, including ongoing analysis, monitoring, and performance tuning, Oversee the testing process to ensure AI solutions meet organizational requirements and deliver expected outcomes., Design and implement Application Lifecycle Management (ALM) processes specifically for AI-powered business solutions, and incorporate responsible AI practices by addressing security, governance, risk management, and compliance considerations throughout the solution lifecycle. Skill-based training lessons include: 1) Analyze Requirements for AI-Powered Business Solutions, 2) Design Overall AI Strategy for Business Solutions, 3) Evaluate the Costs and Benefits of an AI-Powered Business Solution, 4) Design AI and Agents for Business Solutions, 5) Design Extensibility of AI Solutions, 6) Orchestrate Configuration for Prebuilt Agents and Apps, 7) Analyze, Monitor, and Tune AI-Powered Business Solutions, 8) Manage the Testing of AI-Powered Business Solutions, 9) Design the ALM process for AI-Powered Business Solutions, 10) Design the ALM process for AI in Dynamics 365 apps for customer experience and service, and 11) Design Responsible AI, Security, Governance, Risk Management, and Compliance.

Enroll today (teams & executives are welcome): Https://tinyurl.com/yus2du3b

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)

Cisco AI Technical Practitioner 810-110 (Certification)

Colleagues, the “Cisco AI Technical Practitioner - AITECH 810-110” cert program offers practical introduction to generative AI, prompt engineering, AI security and ethics, workflow automation, and agentic AI. Through engaging video lessons, guided demonstrations, hands-on labs, and quiz walkthroughs, you'll develop the knowledge and technical skills needed to confidently deploy and use AI technologies across modern organizations. Whether you're preparing for the Cisco certification exam or looking to build practical AI skills for today's technology workforce, this course provides a comprehensive learning experience focused on real-world implementation and best practices. Learn to: Evaluate AI hosting options and deployment strategies, Apply prompt engineering techniques to improve AI accuracy and consistency, Protect AI systems against prompt injection and other AI-specific security threats, Implement responsible AI principles, governance, and ethical AI practices, Use AI to automate research, software development, and business workflows, Build and orchestrate Agentic AI systems using modern design principles and the Model Context Protocol (MCP), Integrate AI into enterprise environments while balancing performance, security, and cost, and Prepare confidently for the Cisco AI Technical Practitioner (AITECH 810-110) certification exam. Training modules address: 1) Understanding Generative AI Models, 2) Prompt Engineering Fundamentals, 3) Responsible AI, Ethics, and Security, 4) AI for Data Research and Analysis, 5) AI for Software Development and Workflow Automation, 6) Building Agentic AI Systems, and 7) Final Exam Preparation.

Register today (teams & execs are welcome): https://tinyurl.com/3andhxet

Recommended Listening-Reading: 

1 - JavaScript Full Stack Developer: Capture the Job Offer and Advance Your Career (Audible) (Kindle)

2 - AI Software Engineer: ChatGPT, Bard & Beyond (Audible) (Kindle) 

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

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

Microsoft Azure AI Fundamentals (Exam AI-901)

Colleagues, in the “Microsoft Azure AI Fundamentals (Exam AI-901)” program you will validate that candidates understand not just what AI can do, but how to make it do things--deploying models, crafting effective prompts, building lightweight client applications with the Foundry SDK, and creating single-agent solutions. The technology stack covered spans responsible AI principles, generative and agentic AI patterns, text analysis, speech recognition and synthesis, computer vision, image generation, and information extraction via Azure Content Understanding. Learn How To: Describe and apply the six principles of responsible AI in real Azure deployments. Identify the right AI model for a given task: LLMs, small language models, multimodal models, code models, and embedding models. Deploy models in the Foundry portal and interact with them through effective system and user prompts. Build a lightweight chat client application using the Foundry SDK. Create and test single-agent solutions in the Foundry portal, then build client applications for agents. Implement text analysis, speech recognition, and speech synthesis using Foundry. Interpret visual input and generate images using deployed multimodal models. And extract information from documents, images, audio, and video using Azure Content Understanding. Skill-based lessons include: 1) Identify AI Workloads and Common Scenarios, 2) How Generative AI Models Work and How to Choose Them, 3) Responsible AI: Fairness, Reliability and Safety, Privacy and Security, 4) Responsible AI: Inclusiveness, Transparency, Accountability, 5) Text Analysis and Speech Concepts, 6) Computer Vision and Image-Generation Concepts, 7) Information Extraction Concepts, 8) Tour Microsoft Foundry and Deploy Your First Model, 9) Craft Effective System and User Prompts, 10) Build a Lightweight Chat Client Application with the Foundry SDK, 11) Create and Test a Single-Agent Solution in the Foundry Portal, and 12) Extract Information from Documents, Images, Audio, and Video with Content Understanding. You will also build: Lightweight Client Application for an Agent, Text Analysis Application with Foundry, Speech-Enabled Application with Azure Speech in Foundry Tools, and Computer Vision and Image-Generation Application.

Enroll today (teams & executives are welcome): https://tinyurl.com/2zrvw7d7 

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)

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

Much career success, AI Academy (kindly subscribe and share with your peers)

Microsoft AI & ML Engineering Professional Certificate

Colleagues, the “Microsoft AI & ML Engineering Professional Certificate” has a key focus on leveraging cloud-based AI & ML services, specifically through Microsoft Azure, where you manage end-to-end workflows. The program concludes with advanced concepts, ethical considerations, and a capstone project. Learn to: Design and Implement AI & ML Infrastructure: Develop environments, including data pipelines, model development frameworks, and deployment platforms. Master AI & ML Algorithms and Techniques: Apply supervised, unsupervised, reinforcement learning, and deep learning methods to solve challenges. Develop Intelligent Troubleshooting Agents: Create AI-powered agents capable of diagnosing and resolving issues autonomously. And leverage Microsoft Azure for AI & ML Workflows: Set up, manage, and optimize the entire AI & ML. You will acquire high-demand skills with: Generative Model Architectures, Supervised Learning, Natural Language Processing, Model Optimization, Data Infrastructure, LLM Application, Data Preprocessing, Responsible AI, Large Language Modeling, Unsupervised Learning, Fine-tuning, Deep Learning, Data Management, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), and Infrastructure Architecture. Tools you will learn include Generative AI, Generative Adversarial Networks (GANs), Microsoft Azure, Model Deployment, and Lifecycle using Azure.

Enroll today (teams & executives are welcome): https://imp.i384100.net/n467LR

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)

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

Much career success, AI Academy (kindly subscribe and share with your peers)

Reinforcement Learning Specialization

Colleagues, in the “Reinforcement Learning Specialization” you will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or to apply AI tools and ideas to real-world problems. Skill-based training modules address: 1) Fundamentals of Reinforcement Learning, 2) Sample-based Learning Methods, 3) Prediction and Control with Function Approximation, and 4) A Complete Reinforcement Learning System (Capstone). Learn to: Build a Reinforcement Learning system for sequential decision making. Understand the space of RL algorithms (Temporal- Difference learning, Monte Carlo, Sarsa, Q-learning, Policy Gradients, Dyna, and more), how to formalize your task as a Reinforcement Learning problem, and how to begin implementing a solution, and how RL fits under the broader umbrella of machine learning, and how it complements deep learning, supervised and unsupervised learning. Acquire high-demand skills involving  Machine Learning, Reinforcement Learning, Decision Intelligence, Model Evaluation, Simulations, Agentic Systems, Systems Development, Artificial Neural Networks, Machine Learning Methods, Feature Engineering, Markov Model, Deep Learning, Artificial Intelligence, Sampling (Statistics), Model Training, Applied Machine Learning, Algorithms, Solution Architecture, Machine Learning Algorithms, and Supervised Learning.

Enroll today (teams & executives are welcome): https://imp.i384100.net/B5d9MW

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)

Operationalizing Machine Learning and Generative AI Solutions (Microsoft Exam AI-300)

Colleagues, the “Operationalizing Machine Learning and Generative AI Solutions - Microsoft Exam AI-300” program will become a successful candidate for this exam and in the field of Machine Learning operations (MLOps) or Generative AI ops (GenAIOps) needs to understand the MLOps infrastructure, workspace infrastructure, automation, how to manage models, and configure agents. These core components and more are covered in this course. Learn how to: Design and implement an MLOps infrastructure, Implement machine learning model lifecycle and operations, Design and implement a GenAIOps infrastructure, Implement generative AI quality assurance and observability, and Optimize generative AI systems and model performance. Skill-based training modules include: 1) Design and implement an MLOps infrastructure - Create and manage resources and assets in a Machine Learning workspace, Implement IaC for Machine Learning, 2) Implement machine learning model lifecycle and operations - Orchestrate model training Implement model registration and versioning, Deploy machine learning models for production environments, Monitor and maintain machine learning models in production, 3) Design and implement a GenAIOps infrastructure - Implement Foundry environments and platform configuration, Deploy and manage foundation models for production workloads, Implement prompt versioning and management with source control, 5) Implement generative AI quality assurance and observability - Configure evaluation and validation for generative AI applications and agents, Implement observability for generative AI applications and agents, and 5) Optimize generative AI systems and model performance - Optimize retrieval-augmented generation (RAG) performance and accuracy, and Implement advanced fine-tuning and model customization.

Enroll today (teams & executives are welcome): https://tinyurl.com/34pewrmj 

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

AI Colleagues, in the “AI Agent Developer Specialization” you will master the skills of an AI Agent Software Developer. According to Lightcast’s™ Job Postings Report developers in this domain have an average annual salary of $169,700. Learn to design, build, and refine intelligent software agents using Python, generative AI, and agentic architectures for real-world applications. Gain hands-on experience developing AI agents using Python, OpenAI tools, and prompt engineering techniques. You’ll learn to design agent architectures, implement tool use and memory, build custom GPTs, and apply best practices for responsible, trustworthy AI. By the end, you’ll be able to create and deploy intelligent software agents for real-world tasks across a range of industries. Build and deploy intelligent AI agents using Python, tools, memory, and reasoning. Create custom GPTs and apply prompt engineering techniques for real-world tasks. Design trustworthy, responsible AI systems aligned with best practices. 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, 3) Prompt Engineering for ChatGPT, and 4) ChatGPT Advanced Data Analysis. You will acquire high-demand skills including Retrieval-Augmented Generation, Data Presentation, LLM Application, Software Development, Agentic Systems, Responsible AI, Ideation, Generative AI Agents, AI Powered Creativity, Verification and Validation, Prompt Patterns, Data Visualization, and Document Management.

Enroll today - teams and execs are welcome: https://imp.i384100.net/e1Bv4D

Much success in your AI career journey, AI Academy (kindly subscribe and share with your colleagues)

Generate Smarter Generative AI Outputs (training)

Colleagues, the “Generate Smarter Generative AI Outputs” program is designed for developers, data scientists, and AI practitioners, this program builds your ability to create, deploy, and optimize generative AI solutions on Google Cloud. It's delivered through three courses: 1) Introduction to AI and Machine Learning on Google Cloud, 2) Introduction to Image Generation, and 3) Vector Search and Embeddings. You will learn to  recognize and apply the data-to-AI technologies and tools provided by Google Cloud, build and deploy generative AI and machine learning models using Vertex AI and Gemini, construct semantic and hybrid search engines using vector embeddings and Vertex AI Vector Search, and design retrieval-augmented generation (RAG) pipelines to create grounded, accurate AI agents.  Dive into the world of image generation and diffusion models. Explore the deep learning techniques behind many of today's most advanced creative AI systems. Understand how these models are inspired by thermodynamics, explore the progression from unconditioned to text-to-image generation, and learn to train and deploy diffusion models using Google Cloud's Vertex AI platform. Discover how to make AI systems more useful through intelligent search. Explore semantic and hybrid search methods using vector embeddings, and learn to design retrieval-augmented generation (RAG) pipelines that minimize hallucinations and improve contextual accuracy. By applying these concepts, you'll build a robust understanding of how to construct AI agents that retrieve and generate information with precision.

Enroll today - teams and execs are welcome: https://edx.sjv.io/WOQOXG

Much success in your AI career journey, AI Academy (kindly subscribe and share with your colleagues)