CS50 Intro to Artificial Intelligence - Python (HarvardX - training)

Colleagues, in the “CS50's Introduction to Artificial Intelligence with Python” course from HarvardX will learn to use machine learning in Python in this introductory course on artificial intelligence. This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, machine learning, large language models, and other topics in artificial intelligence as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own. You will learn graph search algorithms, adversarial search, knowledge representation, logical inference, probability theory, Bayesian networks, Markov models, constraint satisfaction, machine learning, reinforcement learning, neural networks, and natural language processing.

Enroll today (teams & execs welcome): http://edx.sjv.io/qz4bKq 

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)

“Transformative Innovation” Audio and eBook series make a wonderful Christmas gift!

Black Friday Bonanza - Audible & Kindle Book Series (Amazon)

Transformative Innovation series:

 

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) 

Merry Christmas. Order today, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9 

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Colleagues, the “Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning” program is part of the DeepLearning.AI TensorFlow Developer Professional Certificate. Learn best practices for using TensorFlow, a popular open-source machine learning framework. Build a basic neural network in TensorFlow. Train a neural network for a computer vision application. Understand how to use convolutions to improve your neural network. Gain high-demand skills in Computer Vision, Tensorflow and Machine Learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new DeepLearning.AI TensorFlow Developer Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization. Skill-based training modules include: 1) A New Programming Paradigm, 2) Introduction to Computer Vision, 3) Enhancing Vision with Convolutional Neural Networks, and 4) Using Real-world Images. 

Enroll today (teams & execs welcome): http://imp.i384100.net/21ZjKD 

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 Specialization

Colleagues, in the “Deep Learning Specialization” you will master the fundamentals of deep learning and break into AI. Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications. Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow. Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data. Train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering. Acquire high-demand skills in Recurrent Neural Networks, Tensorflow, Convolutional Neural Networks, Artificial Neural Networks, Transformers, LSTMs, Dropout, BatchNorm and Xavier/He initialization. Training modules include: 1) Neural Networks and Deep Learning, 2) Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, 3) Structuring Machine Learning Projects, 4) Convolutional Neural Networks and 5) Sequence Models.

Enroll today (teams & execs welcome): https://imp.i384100.net/EK3BjP 

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)

AI for Everyone (training)

Colleagues, the AI for Everyone course is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. Learn the meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science, What AI realistically can--and cannot--do, How to spot opportunities to apply AI to problems in your own organization, What it feels like to build machine learning and data science projects, How to work with an AI team and build an AI strategy in your company and How to navigate ethical and societal discussions surrounding AI. Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI. Skill-based lessons include: 1) What is AI? Machine Learning?, What is data?, The terminology of AI, What makes an AI company?, What machine learning can and cannot dos, More examples of what machine learning can and cannot dos, Non-technical explanation of deep learning, 2) Building AI Projects - Workflow of a machine learning project, Workflow of a data science project, Every job function needs to learn how to use data, How to choose an AI project, How to choose an AI project, Working with an AI team, Technical tools for AI teams, 3) Building AI In Your Company - Case study: Smart speaker, Case study: Self-driving car, Example roles of an AI team, AI Transformation Playbook, AI Transformation Playbook, AI pitfalls to avoid, Taking your first step in AI, Survey of major AI application areas, Survey of major AI techniques, and 4) AI and Society - A realistic view of AI, Discrimination/Bias, Adversarial attacks on AI, Adverse uses of AI, AI and developing economies, and AI and jobs.  

Enroll today (teams & execs welcome): https://imp.i384100.net/4P4qr9 

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: Convolutional Neural Networks in Python (training)

Colleagues, in the “Deep Learning: Convolutional Neural Networks in Python” program you will learn Tensorflow, CNNs for Computer Vision, Natural Language Processing (NLP), Data Science and Machine Learning. [79 lectures - 13+ hours of training]. Understand convolution and why it's useful for Deep Learning and explain the architecture of a convolutional neural network (CNN). Implement a CNN in TensorFlow 2. Apply CNNs to challenging Image Recognition tasks and CNNs to Natural Language Processing (NLP) for Text Classification (e.g. Spam Detection, Sentiment Analysis). Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion. Skill-based training lessons include: 1) Google Colab, 2) Machine Learning and Neurons, 3) Feedforward Artificial Neural Networks, 4) Convolutional Neural Networks, 5) Natural Language Processing (NLP), 6) Convolution In-Depth, 7) Convolutional Neural Network Description, 8) Practical Tips, 9) Loss Functions, 10) Gradient Descent, 11) Setting Up Your Environment (FAQ by Student Request), 12) Extra Help With Python Coding for Beginners, and 13) Effective Learning Strategies for Machine Learning.. 

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

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) (Kindle)

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

Generative AI for Software Development Skill Certificate (DeepLearning.AI)

Colleagues, the “Generative AI for Software Development Skill Certificate” will enhance your skills as a software developer, grow your career, and stay competitive in this fast-paced industry. Join some 13,399 students already enrolled. 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. Experiment quickly. Using LLMs can speed up your ability to prototype and test new features, allowing you to quickly iterate and ship your code. Optimize your code quality. Get to production-ready code faster by working with an LLM to find and fix bugs. Team up with AI on engineering tasks. Break through roadblocks and with your team by leveraging an LLM’s knowledge of development roles and tasks. Gain highly marketable skills in Software Engineering, Large Language Models, Software Development, Generative AI and Machine Learning. Skill-based training modules address: 1) Introduction to Generative AI for Software Development, 2) Team Software Engineering with AI, and 3) AI-Powered Software and System Design. Plus, the Applied Learning Project includes: Pair-coding with an LLM to efficiently modify data structures for use in production and at big data scales. Work with an LLM as a skilled software tester to identify bugs, create edge case tests, and update code to correct errors. And Implement a functioning local database from scratch, and partner with an LLM to think through software design issues and how to optimize for efficient, secure data access.

Enroll today (teams & executives are welcome): https://imp.i384100.net/LKP7g3 

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) (Kindle)

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