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)

Convolutional Neural Networks (training)

AI colleagues, in the “Convolutional Neural Networks” you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI. Acquire highly marketable skills including: Facial Recognition System, Tensorflow, Convolutional Neural Network, Deep Learning and Object Detection and Segmentation. Training modules address: 1) Foundations of Convolutional Neural Networks, 2) Deep Convolutional Models: Case Studies, 3) Object Detection, and 4) Special Applications: Face recognition and Neural Style Transfer.

Enroll today (teams & execs welcome): imp.i384100.net/zN7MDW

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 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://tinyurl.com/49f59efr 

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)

Machine Learning Specialization

Colleagues, the Machine Learning Specialization taught by Andrew Ng is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. BreakIntoAI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program. Gain high demand skills in Logistic Regression, Artificial Neural Network, Linear Regression, Decision Trees and Recommender Systems. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization 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. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression. 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. Build and use decision trees and tree ensemble methods, including random forests and boosted trees. 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. Build a deep reinforcement learning model. Skill-based lessons include: 1) Supervised Machine Learning: Regression and Classification, 2) Advanced Learning Algorithms and 3) Unsupervised Learning, Recommenders, Reinforcement Learning.

Enroll today (teams & execs welcome): https://tinyurl.com/yc5c8snp 

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)