Introduction to Generative AI for Software Development (training)

Developers, in the “Introduction to Generative AI for Software Development” program you will learn to Integrate generative AI in development. Learn to use generative AI tools from initial design to deployment, enhancing your efficiency and creativity, Optimize your code quality. Improve your coding, if you’re just starting and need help fixing bugs or an experienced developer breaking new ground, Experiment quickly - Using LLMs can speed up your ability to prototype and test new features, allowing you to quickly iterate and ship your code, Learn how LLMs work. By knowing how machine learning systems work, you’ll be able to use them more effectively to support your work as a developer. Gain highly marketable skills involving Prompting best practices for software development, Assigning an LLM a role or persona, Designing data structures for real world deployment at scale, Analyzing code with an LLM, and Pair-coding with an LLM. Skill-based training lessons cover: 1) Introduction to Generative AI, 2) Pair-coding with an LLM, and 3) Leveraging an LLM for code analysis. By the end of this course, you will be able to: Understand the differences between machine learning and traditional software development. Describe how large language models generate text. Prompt an LLM to assist in the tasks that make up the software developer role. Guide an LLM to complete a task in a specific way by writing detailed prompts and iterating to improve output. Leverage the depth of software development knowledge encoded in an LLM by prompting it to assume specific job roles or personas. Write code quickly using an LLM as a pair-coding partner. And Analyze code for efficiency, security, and performance using an LLM. 

Enroll today (teams & execs welcome): http://imp.i384100.net/RGGkj7 

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)

Natural Language Processing with Python (NLP)

Colleagues, in the “Natural Language Processing with Python (NLP)” program you will learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing. [80 lectures - 11+ training hours]. Work with Text Files with Python and PDF files in Python, utilize Regular Expressions for pattern searching in text, use Spacy for ultra fast tokenization, learn about Stemming and Lemmatization, understand Vocabulary Matching with Spacy, use Part of Speech Tagging to automatically process raw text files, understand Named Entity Recognition, visualize POS and NER with Spacy, use SciKit-Learn for Text Classification, use Latent Dirichlet Allocation for Topic Modelling, learn about Non-negative Matrix Factorization, use the Word2Vec algorithm, NLTK for Sentiment Analysis, and Deep Learning to build out your own chat bot. Skill-based training lessons address: 1) Python Text Basics, 2) Natural Language Processing Basics, 3) Part of Speech Tagging and Named Entity Recognition, 4) Text Classification, 5) Semantics and Sentiment Analysis, 6) Topic Modeling, and 7) Deep Learning for NLP.

Enroll today (teams & execs welcome): https://tinyurl.com/yudx985p

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)

Deep Learning: Advanced Computer Vision (GANs, SSD)

AI Colleagues, in the “Deep Learning: Advanced Computer Vision (GANs, SSD)” program you will learn VGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs +More in Tensorflow, Keras, and Python. [116 lectures - 16+ hours of training]. Understand and apply transfer learning, convolutional neural nets such as VGG, ResNet and Inception, object detection algorithms like SSD, apply neural style transfer, computer vision topic, Class Activation Maps, GANs (Generative Adversarial Networks), Object Localization Implementation Project, and understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion. Skill-based training modules include: 1) Google Colab & Getting Setup, 2) Machine Learning Basics, 3) Artificial Neural Networks (ANN), 4) Convolutional Neural Networks (CNN) Review, 5) VGG and Transfer Learning, 6) ResNet (and Inception), 7) Object Detection (SSD / RetinaNet), 8) Neural Style Transfer, 9) Class Activation Maps, 10) GANs (Generative Adversarial Networks), 11) Object Localization Project, 12) Keras and Tensorflow 2 Basics, 13) With Python Coding for Beginners, and 14) Effective Learning Strategies for Machine Learning.

Enroll today (teams & execs welcome): https://tinyurl.com/36cvnnr4 

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)

Programming Generative AI (training)

Colleagues, the “Programming Generative AI” training provides a hands-on tour of deep generative modeling, taking you from building simple feedforward neural networks in PyTorch all the way to working with large multimodal models capable of simultaneously understanding text and images. Along the way, you will learn how to train your own generative models from scratch to create an infinity of images, generate text with large language models similar to the ones that power applications like ChatGPT, write your own text-to-image pipeline to understand how prompt- based generative models actually work, and personalize large pretrained models like stable diffusion to generate images of novel subjects in unique visual styles. You will learn how to: Train a variational autoencoder with PyTorch to learn a compressed latent space of images. Generate and edit realistic human faces with unconditional diffusion models and SDEdit. Use large language models such as GPT2 to generate text with Hugging Face Transformers. Perform text-based semantic image search using multimodal models such as CLIP. Program your own text-to-image pipeline to understand how prompt-based generative models such as Stable Diffusion actually work. Properly evaluate generative models, both qualitatively and quantitatively. Automatically caption images using pre-trained foundation models Generate images in a specific visual style by efficiently fine-tuning Stable Diffusion with LoRA. Create personalized AI avatars by teaching pretrained diffusion models new subjects and concepts with Dreambooth. Guide the structure and composition of generated images using depth- and edge- conditioned ControlNets. And perform near real-time inference with SDXL Turbo for frame-based video-to-video translation. Skill-based training modules address: 1) The What, Why, and How of Generative AI, 2) PyTorch for the Impatient, 3) Latent Space Rules Everything Around Me, 4) Demystifying Diffusion, 5) Generating and Encoding Text with Transformers, 6) Connecting Text and Images, and 7) Post-Training Procedures for Diffusion Models.

Enroll today (teams & execs welcome): https://tinyurl.com/yck2k9mt 

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)

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

Friends, the new “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle) book is the latest entry to the “Transformative Innovation” series. AI in all of its manifestations represents a bona fide “generational change” of human society as we know it. AI, like many of the historic innovations of the past, has the unsurpassed potential to impact the human race for both good and evil.  All humanity has a vested interest in ensuring the impact of AI is positive. The alternative is unfathomable: A dystopian environment leading to the destruction of mankind in a Noahic antediluvian episode of human culture by the hands of man himself or the divine, omnipotent hand of our sovereign Creator.

This book has a “5 Star” rating on Amazon. Reader comment “If you're curious about how AI works, how it's changing the world, and what might happen next, this book is great. It's a bit like a guide that helps you understand this complex topic. It's a journey that could open your mind to new ideas and change how you see the world.”

Table of Contents:

I - Introduction

II - The Birth of Artificial Intelligence (AI)

III - AI Research and Development

IV - The AI Quantum Multiplier

V - Technological Synergy

VI - The Ethics of Artificial Intelligence

VII - The Global Race for AI Supremacy

VIII - Understanding Artificial General Intelligence (AGI)

IX - Approaches to AGI Development

X - The Era of Artificial Superintelligence (ASI)

XI - Ensuring Safety in AGI and ASI

XII  - AGI and ASI Impact on Society and the Economy

XIII - AI Singularity (“Technological Singularity”)

XIV - Looking Beyond the Singularity

XV - Conclusions

Our journey will examine the birth of AI, the pending transition to Artificial General Intelligence, the era of Artificial Super Intelligence and thoughts on the possibility of AI (or “Technological”) Singularity. Although some of these topics have verifiable, concrete answers, overall, the pendulum rapidly swings from the domain of the known to the domain of the unknown and speculative in the concluding chapters. Our commitment is to amplify the known (factual) elements of Artificial Intelligence and only when necessary delve into the realm of the unknown (subjective) aspects of AI Singularity … and beyond.

Join us for a journey that will transform your thinking and possibly your life!

Order today:

Audible (https://tinyurl.com/3pswj5sx) 

Kindle (https://www.amazon.com/dp/B0CG536WDN)   

3 Book Series: “Transformative Innovation”: 

 

1 - ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity (Audible) (Kindle)

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

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

Thank you for dropping a brief review on this book’s Audible or Kindle page.

Regards, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9 

Mathematics for Machine Learning Specialization

Colleagues, in the “Mathematics for Machine Learning Specialization” from the Imperial College London you will gain high-demand skills with Eigenvalues And Eigenvectors, Principal Component Analysis (PCA), Multivariable Calculus, and Linear Algebra. Get up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science.In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data. It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting. The third course, Dimensionality Reduction with Principal Component Analysis, uses the mathematics from the first two courses to compress high-dimensional data. This course is of intermediate difficulty and will require Python and numpy knowledge. At the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning. Skill-based training modules address: 1) Machine Learning: Linear Algebra, 2) Machine Learning: Multivariate Calculus, and 3) Machine Learning: PCA. 

Enroll today (teams & execs welcome): https://imp.i384100.net/APPX1N 

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)