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)

Natural Language Processing with Python

Colleagues, in the “Natural Language Processing with Python” training program you will learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing. [80 lectures • 11 hours of training]. Learn to work with Text Files with Python and how to work with 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 and 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 cover: 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 & executives are welcome): https://tinyurl.com/mrcauakr

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)

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 A-Z: AI, Python & R + ChatGPT Prize

Colleagues, in the “Machine Learning A-Z: AI, Python & R + ChatGPT Prize” program you will learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included. Master Machine Learning on Python & R. Have a great intuition of many Machine Learning models. Make accurate predictions and powerful analysis. Make robust Machine Learning models. Create strong added value to your business. Use Machine Learning for personal purposes. Handle specific topics like Reinforcement Learning, NLP and Deep Learning along with advanced techniques like Dimensionality Reduction. Learn which Machine Learning model to choose for each type of problem. Skill-based training modules include: 1) Data Preprocessing, 2) Regression, 3) Classification, 4) Clustering, 5) Association Rule Learning, 6) Reinforcement Learning, 7) Natural Language Processing, 8) Deep Learning, 9) Dimensionality Reduction, and 10) Model Selection & Boosting.

Enroll today (teams & executives are welcome): https://tinyurl.com/bdzbu74u 

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)

Structuring Machine Learning Projects (DeepLearning.AI)

Colleagues, the “Structuring Machine Learning Projects” will equip you to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. Gain highly marketable skills in Decision-Making, Machine Learning, Deep Learning, Inductive Transfer and Multi-Task Learning. Training modules address: 1) ML Strategy (Part I): Streamline and optimize your ML production workflow by implementing strategic guidelines for goal-setting and applying human-level performance to help define key priorities - Why ML Strategy, Orthogonalization, Single Number Evaluation Metrics, Satisficing and Optimizing Metric, Train/Dev/Test Distributions, Size of the Dev and Test Sets, When to Change Dev/Test Sets and Metrics?, Why Human-level Performance?, Avoidable Bias, Understanding Human-level Performance, Surpassing Human-level Performance and Improving your Model; and Performance; and 2) ML - Strategy (Part II): Develop time-saving error analysis procedures to evaluate the most worthwhile options to pursue and gain intuition for how to split your data and when to use multi-task, transfer, and end-to-end deep learning - Carrying Out Error Analysis, Cleaning Up Incorrectly Labeled Data, Build your First System Quickly, then Iterate, Training and Testing on Different Distributions, Bias and Variance with Mismatched Data Distributions, Addressing Data Mismatch, Transfer Learning, Multi-task Learning, What is End-to-end Deep Learning?, and Whether to use End-to-end Deep Learning. 

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

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)