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Monday, January 6, 2025

Artificial Intelligence - Discover the Top 3 Career & Earnings Growth Strategies for 2025

Colleagues, on average an AI Software Engineer earns $161k USD in the US according to Glassdoor. The first strategy is to Get Certified: A high quality cert from a reputable vendor or professional association can boost your income by 10%+. Topping our list is the “Generative AI for Everyone” program taught by AI pioneer Andrew Ng (437k students enrolled). Second is the Artificial Intelligence A-Z: Build 7 AI + LLM & ChatGPT, the most popular AI course on Udemy. Coming in third is Introduction to Artificial Intelligence with Python from HarvardX with some 1.9m enrollees. Second, Get Published: Write a series of posts or articles on Best Practices, Industry Trends and Emerging Technologies, and publish on DevPlan’s GCP portal, Medium, LinkedIn Articles, Reddit or Technology.org. Then reate a “project portfolio” on GitHub or LinkedIn that showcases your hands-on expertise. A high quality portfolio proves your expertise to future employers and gives you a competitive advantage over other job candidates. Then reate a “project portfolio” on GitHub or LinkedIn that showcases your hands-on prowess. A high quality portfolio proves your expertise to future employers and gives you a competitive advantage over other job candidates. And third, Get Connected: Professional networking and referrals are the most effective method for landing your dream job - within your current employer or at a new company (rather than simply applying for jobs online and standing in the Human Resources queue with the masses). Join and participate in 2-3 high profile groups or professional associations. Examples include: Hugging Face, Discord and Reddit’s AI sub-Reddit.

Get started today by enrolling in one or more training-certification programs:



Success awaits you! Lawrence E. Wilson - AI Academy (share & subscribe)


Sunday, January 5, 2025

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)


Saturday, January 4, 2025

Supervised Machine Learning: Regression and Classification

Colleagues, in the “Supervised Machine Learning: Regression and Classification” program you will build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn, and train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression. Develop high-demand skills in Linear Regression, Regularization to Avoid Overfitting, Logistic Regression for Classification, Gradient Descent, and Supervised Learning. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn 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. Training modules: Week 1: Introduction to Machine Learning - Applications of machine learning, Supervised learning, Supervised learning, Unsupervised learning, Jupyter Notebooks, Linear regression model, Cost function formula and intuition, Visualizing the cost function, Gradient descent, Implementing gradient descent, Learning rate, Gradient descent for linear regression, and Running gradient descent; Week 2: Regression with multiple input variables - learn some methods for improving your model's training and performance, such as vectorization, feature scaling, feature engineering and polynomial regression. At the end of the week, you'll get to practice implementing linear regression in code; and Week 3: Classification - predict categories using the logistic regression model. You'll learn about the problem of overfitting, and how to handle this problem with a method called regularization. You'll get to practice implementing logistic regression with regularization. 


Enroll today (teams & execs welcome): https://imp.i384100.net/555bxN


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)


Thursday, January 2, 2025

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)


Tuesday, December 24, 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)


Monday, December 23, 2024

Christmas Bonanza - Audible & Kindle Book Series (Amazon)

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

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 


The Deep Learning - Career Accelerator (July 7)

Colleagues, our goal is to provide Deep Learning professionals with actionable information to advance your career and income growth: Market ...