AI Academy

Monday, May 27, 2024

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)

Become a Certified ChatGPT Expert

Colleagues, unleash the potential of Artificial Intelligence (AI) in your career with the Certified ChatGPT Expert Certification program. ChatGPT, developed by OpenAI, is no mere language processing tool – it’s a ground-breaking AI technology that’s reshaping our interactions with the world. The innovative natural language processing capabilities of ChatGPT are already setting the pace in sectors like customer service, marketing, advertising, and healthcare. As we stride forward into an increasingly digital era, the need for AI professionals versed in ChatGPT is surging. By becoming a Certified ChatGPT Expert, you position yourself at the vanguard of this swiftly evolving field. The Certified ChatGPT Expert Certification program is your ticket to mastering this revolutionary AI tool. Skill-based training lessons include: 1) Introduction to ChatGPT and AI - The history of ChatGPT, Applications of ChatGPT, ChatGPT vs other chatbot platforms, Industries using ChatGPT, The benefits and limitations of ChatGPT, Future developments in ChatGPT technology, Ethical considerations related to ChatGPT and AI; 2) AI and Machine Learning Concepts for ChatGPT - Types of AI, What is Machine Learning?, Neural Networks, Deep Learning, Natural Language Processing (NLP), Computer Vision, Robotics and AI; 3) Types of AI - Narrow AI, Strong AI, Superintelligence, ChatGPT Functionalities and Working, How does ChatGPT work?, ChatGPT 3 vs ChatGPT 4, ChatGPT Functionalities, Drafting emails and professional communication, Automating content creation, Research and information gathering, Brainstorming ideas and creative problem solving, Best Practices for Using ChatGPT; 4) ChatGPT Prompt Engineering - What is Prompt Engineering?, Types of Prompts, Crafting Effective Prompts, Using ChatGPT to generate prompt, Evaluating Prompt Effectiveness; 5) Working with OpenAI API - Overview of OpenAI API, ChatGPT PlayGround, How to setup ChatGPT add-on, Get started with ChatGPT in Google Docs, Get started with ChatGPT in Google Sheets, Data generation trick for ChatGPT in Google Sheets, Text Analytics using ChatGPT; 5) Customize ChatGPT; 6) Data Privacy with ChatGPT - Challenge of data privacy, Mitigating data leakage using data masking, Using Private Large Language Models; and 7) ChatGPT Job Opportunities - Introduction to ChatGPT Job Opportunities, Job Search Strategies and Resources, Resume and Interview Preparation, ChatGPT: Freelance and Entrepreneurial Opportunities, and Challenges and Opportunities in the Field of ChatGPT. Followed by your certification exam.

Enroll today (teams & execs welcome): https://tinyurl.com/4fznk89v

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” (Kindle) or (Audible - coming soon!)

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

Thursday, May 23, 2024

AI Software Engineer: ChatGPT, Bard and Beyond (audio & ebook)

Colleagues, the purpose of the “AI Software Engineer: ChatGPT, Bard and Beyond” (Interview Prodigy series) help software engineers and developers capture their ideal job offer and manage their medium-to-long-term career growth in the global artificial intelligence arena. We will focus on artificial intelligence software engineers and developers in this series. Artificial intelligence has proven to be a revolutionary part of the digital era. As a result, top tech giants like Amazon, Google, Apple, Facebook, Microsoft, and International Business Machines Corporation have been investing significantly in the research and development of artificial intelligence. As a result, these companies are contributing well to making A.I. more accessible for businesses. In addition, different companies have adopted A.I. technology for improved customer experience. For example, in March 2020, McDonald's invested $300 million to acquire an A.I. startup in Tel Aviv to provide a personalized experience for its customers using artificial intelligence. This was its most significant tech investment.

AI Engineers have many opportunities, which will only grow with time. After reading this book, I hope you can identify your ideal job offer and manage your short- and long-term career growth plan, especially in artificial intelligence. The world of artificial intelligence is vast. As I stated earlier in this book, it has a current market size of $136.55 billion based on a 2022 report by CAGR, and it will likely reach a growth rate of 37.3% from 2023 to 2030. You can study artificial intelligence from three aspects. First, the narrow artificial intelligence: this is where you learn about strong AI, artificial general intelligence, and narrow artificial intelligence, also known as weak AI. As I mentioned earlier in this book, the tech we use daily is known as narrow artificial intelligence mainly because it focuses on one narrow task. An example is a chess computer, Siri, or Alexa. Artificial narrow intelligence generally operates within a limited predetermined range. Then there is machine learning, an application that allows systems and computers to learn and improve without being programmed. This idea aims to enable systems to learn and adapt automatically without human involvement or support. Deep learning enables inventors to enhance technology such as self-driving vehicles, speech recognition, and facial identification.

Order today:

(Audible) https://tinyurl.com/mae9ku3b

(Kindle) https://tinyurl.com/27jux34w

Transformative Innovation (book series):

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 (Audible) (Kindle)

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

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

Machine Learning Engineer with Microsoft Azure

Colleagues, students of the Machine Learning Engineer with Microsoft Azure will gain experience in understanding ML models, protecting people and their data, and controlling the end-to-end ML lifecycle at scale. Develop high-demand and highly marketable skills involving Azure Machine Learning, Azure data services, AI business context, Azure ML platform, Azure ML pipelines, Open neural network exchange, Hyperparameter tuning, Azure ML designer, Model interpretation, Azure ML sdk, Azure ML experiments, Model maintenance, Cloud asset management, Azure ml automated ML, Kubernetes security, Azure ML pipelines, API troubleshooting, REST APIs, Deployment testing, Azure kubernetes service, Swagger, Docker and ApacheBench. Learning modules include: 1) Welcome to Machine Learning Engineer with Microsoft Azure - learn more about the pre-requisites, structure of the program, and getting started, 2) Machine Learning Engineer Program Introduction, the structure of the program and meet your instructors, 3) Using Azure Machine Learning - learn how to configure machine learning pipelines in Azure, identify use cases for Automated Machine Learning, and use the Azure ML SDK to design, create, and manage machine learning pipelines in Azure, 4) Introduction to Azure ML - learn about Machine Learning in the cloud and how workspaces and AzureML studio enable you to be more productive as a data scientist or ML engineer, 5) Datastores and Datasets - learn how to integrate third party datasets and open datasets into our ML pipeline to quickly develop working solutions, 6) Training Models in Azure ML - learn how to manage pipelines and use hyperparameters in experiments, as well as how to automate changes that create huge value in terms of prediction accuracy, 7) The AzureML SDK - programmatically create and manage pipelines. We'll see that this approach makes pipeline creation and management a reproducible process, Automated ML and Hyperparameter Tuning, 8) Optimizing an ML Pipeline in Azure - create and optimize an ML pipeline. You'll do this using both HyperDrive and AutoML, so that you can compare the results, 9) Machine Learning Operations This course covers a lot of the key concepts of operationalizing Machine Learning, from selecting the appropriate targets for deploying models, to enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines. All these concepts are part of core DevOps pillars that will allow you to demonstrate solid skills for shipping machine learning models into production, 10) Operationalizing Machine Learning - work with the Bank Marketing dataset. You will use Azure to configure a cloud-based machine learning production model, deploy it, and consume it, and Capstone - Azure Machine Learning Engineer - this capstone project gives you the opportunity to use the Azure Machine learning knowledge you have obtained from this Nanodegree to solve the problem of your interest.

Enroll today (teams & executives are welcome): https://fxo.co/IJ2h

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

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

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

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

Wednesday, May 22, 2024

“The Promise of Data-Driven Decision Making - From Analytics to Visualization and Beyond” (new audio & ebook)

Colleagues, “The Promise of Data-Driven Decision Making” is a powerful resource that has the potential to transform the way we approach problem-solving in both our personal and professional lives. By collecting and analyzing data, we can gain valuable insights into the world around us, and use that knowledge to make more informed decisions. Throughout this book, we have explored the various aspects of data-based decision making, including the benefits, challenges, and best practices. We have also examined the different tools and techniques that can be used to collect and analyze data, as well as the ethical considerations that must be taken into account.

Highly data-driven firms are three times more likely to report a major improvement in decision making, according to a large decision survey conducted by PWC. However, only one in three CEOs claim that their company is heavily data-driven. It comes up frequently in meetings with corporate leaders that executives have instant access to large volumes of data. We also learn that their personal intuition or gut feeling plays a significant role in their decision-making. How might the art and science of decision-making be combined better? A more efficient use of data and the capacity to draw insights are seen to present potential for enterprises to generate higher value. Analytics may support an organization's growth and innovation, increase productivity, and improve risk management when they are integrated into the culture of decision-making within the company. The use of facts, metrics, and data to inform strategic business decisions that are in line with a company's goals, objectives, and activities is known as data-driven decision-making. Interactive dashboards, work management platforms, and OKR tools are examples of modern analytics tools that assist individuals overcome prejudice and make the best management decisions that are in line with business strategies. Instead of making decisions based on intuition, opinion, or personal experience, it compiles historical data to examine trends and make better decisions for the future in relation to what has previously worked.

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9)

Or read now on Kindle (https://tinyurl.com/hptundzs)

This book is part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

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