Machine Learning DevOps Engineer (training)

Colleagues, the Machine Learning DevOps Engineer training program will equip you to streamline the integration of machine-learning models and deploy them to a production environment. Acquire core skills in Clean Code Principles, Building a Reproducible Model Workflow, Deploying a Scalable ML Pipeline in Production plus ML Model Scoring and Monitoring. Training modules include: 1) Introduction to Machine Learning DevOps Engineer - develop skills that are essential for deploying production machine learning models. First, you will put your coding best practices on auto-pilot by learning how to use PyLint and AutoPEP8. Then you will further expand your git and Github skills to work with teams. Finally, you will learn best practices associated with testing and logging used in production settings in order to ensure your models can stand the test of time, 2) Clean Code Principles, 3) Building a Reproducible Model Workflow - become more efficient, effective, and productive in modern, real-world ML projects by adopting best practices around reproducible workflows. Learn the fundamentals of MLops and how to: a) create a clean, organized, reproducible, end-to-end machine learning pipeline from scratch using MLflow b) clean and validate the data using pytest c) track experiments, code, and results using GitHub and Weights & Biases d) select the best-performing model for production and e) deploy a model using MLflow. It also touches on Kubernetes, Kubeflow, and Great Expectations and how they relate to the content of the class, 3) Deploying a Scalable ML Pipeline in Production - deploy a machine learning model into production. En route to that goal students will learn how to put the finishing touches on a model by taking a fine grained approach to model performance, checking bias, and ultimately writing a model card. Students will also learn how to version control their data and models using Data Version Control (DVC). Continuous Integration and Continuous Deployment is also covered which will be accomplished using GitHub Actions and Heroku, respectively. Finally, students will learn how to write a fast, type-checked, and auto-documented API using FastAPI, and 4) ML Model Scoring and Monitoring - automate the devops processes required to score and re-deploy ML models. Students will automate model training and deployment. Students will learn to diagnose operational issues with models, including data integrity and stability problems, timing problems, and dependency issues, and learn to set up automated reporting with API’s.

Enroll today (teams & executives are welcome): https://tinyurl.com/4358bm9v 

Download your free AI-ML-DL - Career Transformation Guide.

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) https://tinyurl.com/mae9ku3b or (Kindle) https://tinyurl.com/27jux34w 

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible (https://tinyurl.com/bdfrtyj2) or ebook on Kindle (https://tinyurl.com/jfntsyj2) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Kindle) https://tinyurl.com/4bmmad9k  (Audible - coming soon!)

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

“ChatGPT … ChatGPT, Bard and Beyond” (new audio & ebook)

Colleagues, the new book “ChatGPT … ChatGPT, Bard and Beyond” (Audible) (Kindle) explores how generative conversational AI has the potential to improve accessibility for people with disabilities and those who struggle with language barriers, as AI models can be trained to understand and respond to a wide range of languages and dialects. Listen or read this new book now on Amazon. Generative conversational AI represents a major shift in how we interact with technology and has the potential to improve many aspects of our lives, from customer service and support to healthcare and accessibility. ChatGPT is a specific implementation of Generative conversational AI technology developed by OpenAI. It is a large language model trained on vast text data, allowing it to generate human-like responses to text inputs. In the context of conversational AI, ChatGPT can be used to build chatbots, virtual assistants, and other applications that require the ability to generate text in real time. The model's size and training data allow it to develop highly relevant and human-like text, making it well-suited for various applications. As a state-of-the-art Generative conversational AI, ChatGPT is the perfect tool for organizations looking to step up their communication game. Whether you want to improve interactions with customers, employees, or other stakeholders, ChatGPT makes it easy. Want to see just how much you can achieve with this powerful tool? Key topics include: 1) ChatGPT History and Development, 2) The Technology Underlying ChatGPT, 3) Applications of ChatGPT in Natural Language Processing and Generation, 4) Using ChatGPT for Language Translation and Summarization, 5) ChatGPT in Dialogue Systems and Conversational AI, 6) Ethics and Limitations of ChatGPT, 7) Future Developments and Advancements in ChatGPT, 8) The Impact of ChatGPT on Society, and 9) Conclusions and Next Steps.

Access the Transformative Innovation book series on Amazon today!

 

1 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) (Kindle) 

2 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Kindle) (Audible - coming soon!)

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

Regards, Genesys Digital (Amazon Author Page)

Become an AI Product Manager (Nanodegree Program)

Colleagues, in the “AI Product Manager” (Nanodegree Program) you will learn to develop AI products that deliver business value while building  skills that help you compete in the new AI-powered world. Learn how to evaluate the business value of an AI product. You’ll start by building familiarity and fluency with common AI concepts. You’ll then learn how to scope and build a data set, train a model, and evaluate its business impact. Finally, you’ll learn how to ensure a product is successful by focusing on scalability, potential biases, and compliance. Along the way, you’ll review case studies and examples to help you focus on how to define metrics to measure the business value for a proposed product. Training modules and hands-on projects involve: 1) Introduction to AI in Business - gain foundational knowledge of AI and machine learning, how to develop a business case for an AI application, and how and when to use AI in a product. A high-quality training data set is essential for machine learning models. Learn how to create a high-quality dataset, including how well the data fits a particular use case (Project: Create a Medical Image Annotation Data Set with Appen), 2) Building a Model - understand how neural networks produce a decision and how “training” works. You’ll also learn how to use training data and how to evaluate the results of a model (Project: Build a Model with Google AutoML), and 3) Measuring Impact and Updating Models - learn how to measure post-deployment impact, and how to make data-informed improvements on your model. You’ll also learn how to avoid unwanted bias, ensure security and compliance, and how to scale your product (Capstone Project).

Enroll today (teams & executives are welcome): https://tinyurl.com/3u8n666x 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to or read our related AI books on Amazon”

• ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity (Kindle) (Audible - coming soon!)

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

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

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

Become a Natural Language Processing Expert

AI Colleagues, become a “Natural Language Processing” expert by mastering the skills to get computers to understand, process, and manipulate human language. Build models on real data, and get hands-on experience with sentiment analysis, machine translation (3 months to complete). Learn cutting-edge natural language processing techniques to process speech and analyze text. Build probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks. Training modules include: 1) Introduction to Natural Language Processing - learn text processing fundamentals, including stemming and lemmatization. Explore machine learning methods in sentiment analysis. Build a speech tagging model (Project: Part of Speech Tagging), 2) Computing with Natural Language - learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures (Project: Machine Translation); and 3) Communicating with Natural Language - learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks (Project: Speech Recognizer).

Enroll today (teams & executives are welcome): https://tinyurl.com/8bc8asms 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ““ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible. (https://tinyurl.com/bdfrtyj2) or 

Read the ebook today on Amazon Kindle (https://tinyurl.com/jfntsyj2) 

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

ChatGPT Fundamentals (training)

AI Colleagues, enroll today in the “ChatGPT Fundamentals” program - a one-of-a-kind educational tool that helps you master the groundbreaking technology of ChatGPT and its applications in content creation. In this course, you will learn the best practices for utilizing ChatGPT to create different types of content. Based on a report by Resume Builder, “49% of companies currently use ChatGPT while another 30% are planning to. Also, 93% of the current users plan to extend their use of ChatGPT.”  The ChatGPT Course is an exclusive training resource that will help you tap into the potential of ChatGPT to serve different business use cases with valuable insights into real-world use cases of ChatGPT prompts with practical demonstrations. With the new ChatGPT Course, you will gain pro-level skills in the field of AI-based writing. Leverage The True Potential Of ChatGPT By Training modules include: 1) Bonus Materials - ChatGPT eBook, Mind Map, ChatGPT Prompt Guide and Link List, 2) ChatGPT and AI Fundamentals - Use Cases for ChatGPT, Role of ChatGPT, Future of ChatGPT, ChatGPT Statistics, Facts & Trends, Limitations, What is a Chatbot?, Understanding AI/ML, Demos: tools to Use with ChatGPT, How to Get Started with ChatGPT, Example Prompts and a discussion of ChatGPT Performance Issues, 2) ChatGPT Prompt Demos - Best practices for writing prompts - Asking Questions, Top Ten Lists,  Long Form Docs, Complex Form and Code, Feedback, Content Modification, Instruction Generation, Information Extraction, Writing Computer Code, Solving Math Problems, Create YT Video Outline, Write a Blog Article, SEO Keywords, Comparing Google Bard vs ChatGPT, and 4) Summary and Final Exam.

Enroll today (teams & executives are welcome): https://tinyurl.com/2vkxav7j 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ““ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible. (https://tinyurl.com/bdfrtyj2) or 

Read the ebook today on Amazon Kindle (https://tinyurl.com/jfntsyj2) 

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

Intermediate Python (Training)

Dev Colleagues, gain practitioner-level skills with “Intermediate Python” and learn the language powering transformation in Data Science, Machine Learning, and beyond (estimated 2 months to complete). Python is the general-purpose coding language with applications in web development, data science, machine learning, fintech and more. The Intermediate Python Nanodegree program equips you to leverage the capabilities of Python and streamline the functionality of applications that perform complex tasks, such as classifying files, data mining a webpage, etc. Prerequisite knowledge - Basic familiarity with programming in Python. Training modules with hands-on projects include: 1) Advanced Python Topics - Python's methods to describe data, then dig deeper into functions and functional design, and create strategies for solving problems. You'll investigate the ins-and-outs of objects and object-based design, obtaining order from the interconnected ideas captured within class objects and instance objects. Finally, you'll have an opportunity to fuse Python with external files, culminating in the creation of complete codebases that can crunch numbers or protect the planet from peril (Project: Near-Earth Objects), 2) Large Codebases with Libraries - learn to write, structure, and extend your code to be able to support developing large systems at scale. Understand how you can leverage open source libraries to quickly add advanced functionality to your code and how you can package your code into libraries of your own. Apply Object Oriented Programming to ensure that your code remains modular, clear, and understandable. Honing these skills are the foundations for building codebases that are maintainable and efficient as they grow to tens of thousands of lines (Project:Meme Generator).

Enroll today (teams & executives are welcome): https://tinyurl.com/2vujw2dk 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ““ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible. (https://tinyurl.com/bdfrtyj2) or 

Read the ebook today on Amazon Kindle (https://tinyurl.com/jfntsyj2) 

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

AI Reinforcement Learning

Colleagues, the AI “Reinforcement Learning” program  introduces you to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in an uncertain environment. Skill-based training modules include: 1) Introduction to Reinforcement Learning the fundamentals of RL and its elements. This module also introduces you to OpenAI Gym - a programming environment used for implementing RL agents, Branches of Machine Learning, What is Reinforcement Learning?, Reinforcement Learning Process, Elements of Reinforcement Learning, RL Agent Taxonomy, Reinforcement Learning Problem, Introduction to OpenAI Gym; 2) Bandit Algorithms and Markov Decision Process - Bandit Algorithms, Markov Process, Reward Process & Decision Process; 3) Dynamic Programming & Temporal Difference Methods - Introduction to Dynamic Programming, Dynamic Programming Algorithms, Monte Carlo Methods, Temporal Difference Learning Methods; and 4) Deep Q Learning - Policy Gradients, Gradients using TensorFlow, Deep Q learning and Q learning with replay buffers, target networks, and CNN along with an in-class project to provide you hands-on experience in Reinforcement Learning.

Enroll today (teams & executives are welcome): https://tinyurl.com/2kdsm5xh 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ““ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible (https://tinyurl.com/bdfrtyj2) or 

Read the ebook today on Kindle (https://tinyurl.com/jfntsyj2) 

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

Supervised Learning (training)

AI-ML Colleagues, the “Supervised Learning” program you will learn to apply a wide range of supervised-learning techniques — from simple linear regression to support vector machines (SVM). Machine learning” sounds intimidating, but in reality it is far more accessible than people think. This course is tailored for both students and professionals looking to improve their understanding of supervised machine learning methods (i.e. regression and classification techniques) so they can run their own predictive algorithms, as well as contribute meaningfully to other teams’ ML projects. In addition to working through a range of hands-on exercises, you’ll also apply what you’ve learned to predict potential donors for a fictional charity based on census data. Training modules & hands-on projects involve: 1) Regression - learn the difference between Regression and Classification, train a Linear Regression model to predict values, and learn to predict states using Logistic Regression, 2) Perceptron Algorithms - learn the definition of a perceptron as a building block for neural networks and the perceptron algorithm for classification, 3) Decision Trees - train Decision Trees to predict states and use Entropy to build decision trees, recursively, 4) Naive Bayes - learn the Bayes’ rule, and apply it to predict cases of spam messages using the Naive Bayes algorithm. Train models using Bayesian Learning and complete an exercise that uses Bayesian Learning for natural language processing, 5) Support Vector Machines - train a Support Vector Machines to separate data, linearly. Use Kernel Methods in order to train SVMs on data that is not linearly separable, 6) Ensemble of Learners - build professional presentations and data visualizations for quantitative and categorical data. Create pie, bar, line, scatter, histogram, and boxplot charts, 7) Evaluation Metrics - calculate accuracy, precision and recall to measure the performance of your models, and 8) Training and Tuning Models - train and test models with Scikit-learn. Choose the best model using evaluation techniques such as cross-validation and grid search. Course Project: “Find Donors for CharityML” - your goal will be to evaluate and optimize several different supervised learning algorithms to determine which algorithm will provide the highest donation yield while under some marketing constraints.

Enroll today (teams & executives are welcome): https://tinyurl.com/mryzxu45 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ““ChatGPT - The Era of Generative Conversational AI Has Begun” audiobook on Audible (https://tinyurl.com/bdfrtyj2) or 

Read the ebook today on Kindle (https://tinyurl.com/jfntsyj2) 

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