AI Foundations for Everyone Specialization

Colleagues, the “AI Foundations for Everyone Specialization” will develop job-ready AI skills in Cloud Computing, Human Computer Interaction, Human Learning, Machine Learning, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, and Computer Programming. You will become acquainted with terms like Machine Learning, Deep Learning and Neural Networks. It will familiarize you with IBM Watson AI services that enable any business to quickly and easily employ pre-built AI smarts to their products and solutions. You will also learn about creating intelligent virtual assistants and how they can be leveraged in different scenarios. Larners will have had hands-on interactions with several AI environments and applications, and have built and deployed an AI enabled chatbot on a website – without any coding. Applied Learning Project: Learners would have developed,  tested, and deployed a Watson AI powered customer service chatbot on a website to delight their clients. Skill-based training modules include: 1) Introduction to Artificial Intelligence (AI), 2) Generative AI: Introduction and Applications, 3) Generative AI: Prompt Engineering Basics, and Building AI Powered Chatbots Without Programming.

Enroll today (teams & execs welcome): https://imp.i384100.net/EEZ42X 

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)

Structuring Machine Learning Projects (training)

Colleagues, the “Structuring Machine Learning Projects” program is part of the Deep Learning Specialization from DeppLearning.AI. Learn 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. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. Gain highly marketable skills in Decision-Making, Machine Learning, Deep Learning, Inductive Transfer, and Multi-Task Learning. Training modules include: 1) ML Strategy - Orthogonalization, Single Number Evaluation Metric, Satisficing and Optimizing Metric, Train/Dev/Test Distributions, Size of the Dev and Test Sets, When to Change Dev/Test Sets and Metric?, Human-level Performance?, Avoidable Bias, Understanding Human-level Performance, Surpassing Human-level Performance, Improving your Model Performance, and Andrej Karpathy Interview; and 2) ML Strategy - Part II - 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?, Whether to use End-to-end Deep Learning, and Ruslan Salakhutdinov Interview. 

Enroll today (teams & execs 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) or (Kindle) 

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

Deep Learning A-Z: Neural Networks, AI & ChatGPT (training)

Colleagues, in the “Deep Learning A-Z: Neural Networks, AI & ChatGPT” program you will learn to create Deep Learning models in Python from two Machine Learning, Data Science experts. Code templates included. [188 lectures • 22+ training hours]. Understand the intuition behind Artificial Neural Networks. Apply Artificial Neural Networks in practice. Understand the intuition behind Convolutional Neural Networks. Apply Convolutional Neural Networks in practice. Understand the intuition behind Recurrent Neural Networks. Apply Recurrent Neural Networks in practice. Understand the intuition behind Self-Organizing Maps. Apply Self-Organizing Maps in practice. Understand the intuition behind Boltzmann Machines. Apply Boltzmann Machines in practice. Understand the intuition behind AutoEncoders. Apply AutoEncoders in practice. Skill-based training lessons include: 1) Artificial Neural Networks - ANN Intuition, Building an ANN, 2) Convolutional Neural Networks - CNN Intuition, Building a CNN, 3) Recurrent Neural Networks  - RNN Intuition, Building a RNN, Evaluating and Improving the RNN, 4) Self Organizing Maps - SOMs Intuition, Building a SOM, Mega Case Study, 5) Boltzmann Machines - Boltzmann Machine Intuition, Building a Boltzmann Machine, 6) AutoEncoders - AutoEncoders Intuition, Building an AutoEncoder, and 7) Get the Machine Learning Basics - Regression & Classification Intuition, Data Preprocessing, Data Preprocessing in Python, and Logistic Regression. 

Enroll today (teams & execs welcome): https://tinyurl.com/bdfe2548 

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

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

Neural Networks and Deep Learning

Colleagues, the “Neural Networks and Deep Learning” program is part of Deep Learning Specialization. You will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. Gain high-demand skills in Artificial Neural Networks, Deep Learning, Machine Learning, Machine Learning Algorithms, Python Programming, Computer Programming, Network Architecture, Network Model, Calculus, Human Learning, Regression, and Mathematics. Skill-based training modules include: 1) Introduction to Deep Learning, 2) Neural Networks Basics, 3) Shallow Neural Networks, and 4) Deep Neural Networks.

Enroll today (teams & execs welcome): https://imp.i384100.net/4POZWZ 

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

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

Introduction to Artificial Intelligence (IBM)

Colleagues, the “Introduction to Artificial Intelligence (AI)” program from IBM will equip you to describe what AI is and explain the core concepts related to AI, demonstrate how AI applications and use cases can transform our lives and our work, recognize the potential and impact of AI to transform businesses and careers, and describe the issues, limitations, and ethical concerns surrounding AI. Artificial Intelligence is all around us, seamlessly integrated into our daily lives and work. Enroll in this course to understand the key AI terminology and applications and launch your AI career or transform your existing one. This course covers core AI concepts, including deep learning, machine learning, and neural networks. You’ll examine generative AI models, including large language models (LLMs) and their capabilities. Furthermore, you’ll examine AI’s application across domains such as natural language processing (NLP), computer vision, and robotics, uncovering how these advancements drive innovation and use cases. The course includes hands-on labs and a project, providing an opportunity to explore AI’s use cases and applications. You will also hear from expert practitioners about the capabilities, applications, and ethical considerations surrounding AI. Skill-based training modules include: 1) Introduction and Applications of AI, 2) AI Concepts, Terminology, and Application Domains, 3) Business and Career Transformation Through AI, and 4) Issues, Concerns, and Ethical Considerations.

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

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)

Generative AI Course: Masters Program (training)

Colleagues, in the “Generative AI Course: Masters Program” (training you will master the principles of Generative AI and implement them in real-world applications. As per ZipRecruiter, the average salary of a Generative AI Engineer is $115,864 per year in the USA [200+ Hours of Interactive Learning - 5+ Projects and 50+ Assignments]. This gen AI online course includes training on Python Programming, Data Science, Artificial Intelligence, Natural Language Processing, Generative AI, Prompt Engineering, ChatGPT, and many more. The curriculum has been meticulously designed by the industry experts based on an analysis of 5000+ global job descriptions. Skill-based training modules cover: 1) Python Programming Certification - master important Python programming concepts such as Data Operations, File Operations, Object-Oriented concepts, 2) Data Science with Python Certification - accredited by NASSCOM, is designed to help you master essential Python programming concepts for Data Science, 3) Artificial Intelligence Certification - will help you prepare for AI Engineer, Data Scientist and NLP Engineer roles, 4) ChatGPT Training Course - effectively interact with the biggest revelation in the ChatGPT. You will be able to upgrade your prompt engineering skills Prompt Engineering with Generative, 5) Prompt Engineering - help you prepare as a Prompt Engineer, NLP Engineer, Chatbot Developer, etc. Generative AI Industry Applications - explore the transformative power of Generative AI through our industry-focused modules. From bolstering fraud detection with GAN models to unleashing artistic creativity with MidJourney. Elective courses include: 1) Python Statistics for Data Science, 2) Reinforcement Learning, 3) Graphical Models Certification, and 4) Sequence Learning Certification Training.

Enroll today (teams & execs welcome): https://tinyurl.com/5yf3ejk4 

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 Specialization

Colleagues, in the “Deep Learning Specialization” you will 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, create 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, and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering. You will be equipped with leading-edge skills involving Machine Learning, Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Network Model, Algorithms, Computer Programming, Computer Vision, Network Architecture, and Human Learning. You will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Applied Learning Project. Training lessons include: 1) Named Entity Recognition and Question Answering, 2) Neural Networks and Deep Learning, 3) Improve Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, 4) Structuring Machine Learning Projects, 5) Convolutional Neural Networks, and 6) Sequence Models. 

Enroll today (teams & execs welcome): https://imp.i384100.net/EK3BjP 

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

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

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Colleagues, in the “Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization” you will develop skills in Applied Machine Learning, Deep Learning, Machine Learning, Artificial Neural Networks, Machine Learning Algorithms, Algorithms, Computer Programming, Mathematics, Python Programming, Mathematical Theory and Analysis, and Human Learning. You will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. 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. Skill-based training modules include: 1) Practical Aspects of Deep Learning, 2) Optimization Algorithms, and 3) Hyperparameter Tuning, Batch Normalization and Programming Frameworks. 

Enroll today (teams & execs welcome): https://imp.i384100.net/LKZ95a 

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

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

Python for Data Science, AI and Development (IBM)

Colleagues, in the “Python for Data Science, AI and Development” training from IBM you will learn Python - the most popular programming language and for Data Science and Software Development. Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes. Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks. Access and web scrape data using APIs and Python libraries like Beautiful Soup. Acquire highly marketable skills with Data Science, Data Analysis, Python Programming, Numpy, and Pandas. Learn more about Outcomes, Modules, Recommendations, Testimonials, Reviews, Browse, Data Science, and Data Analysis. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy and Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles. Skill-based lessons include:1) Python Basics, 2) Python Data Structures, 3) Python Programming Fundamentals, 4) Working with Data in Python, and 5) APIs and Data Collection. 

Enroll today (teams & executives are welcome): https://imp.i384100.net/dOOy2Q

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

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

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

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