IBM AI Developer Professional Certificate

Colleagues, the IBM AI Developer Professional Certificate program will equip you with sought-after expertise in building AI-powered chatbots and apps and enable you to launch your AI career in just 6 months. AI Developers are prized software engineers who design, develop, and implement AI and genAI powered apps And virtual assistants. Master the fundamentals of software engineering, AI, generative AI, prompt engineering, HTML, JavaScript and Python programming. And through hands-on labs and projects, you’ll gain practical experience in building AI apps. Obtain a Professional Certificate from Coursera and a digital badge from IBM that showcase your AI proficiency. And you’ll have access to career assistance, job search, and interview preparation resources. Gain job-ready AI skills in just 6 months, plus practical experience and an industry-recognized certification employers are actively looking for. Learn the concepts, key terms, building blocks, and applications of AI, encompassing generative AI. Learn how to build generative AI-powered apps and chatbots using various programming frameworks and AI technologies and how to use Python and Flask to develop and deploy AI applications on the web. Acquire high-demand highly marketable skills in Voice Assistants, Chatbots, Python Programming, Software Engineering, Software Architecture, Agile and Scrum, Software Development Lifecycle, Coding Challenge, Interview Preparation, Full Stack Development, Artificial Intelligence (AI), ChatGPT, Large Language Models (LLM), Natural Language Generation, Generative AI, Prompt Engineering, Prompt Patterns, Web Development, JavaScript, Cascading Style Sheets (CSS), Application development, Web Application, Flask, Code generation, Data Science and Analysis, Data Analysis, Numpy, Pandas, Machine Learning and Deep Learning. Training lessons address: 1) Introduction to Software Engineering, 2) Introduction to Artificial Intelligence (AI), 3) Generative AI: Introduction and Applications, 4) Generative AI: Prompt Engineering Basics, 5) Introduction to HTML, CSS, & JavaScript, 6) Python for Data Science, AI & Development, 7) Developing AI Applications with Python and Flask, 8) Building Generative AI-Powered Applications with Python, 9) Generative AI: Elevate your Software Development Career, and 10) Software Developer Career Guide and Interview Preparation. 

Enroll today (teams & execs welcome): imp.i384100.net/6e4mE3 

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)

Data Analysis with R Programming (Google)

Colleagues, the Data Analysis with R Programming training will teach you how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Describe the R programming language and its programming environment. Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors. Describe the options for generating visualizations in R. Demonstrate an understanding of the basic formatting in R Markdown to create structure and emphasize content. Obtain crucial skills in Data Analysis, R Markdown, Data Visualization, R Programming and RStudio. Training modules include: 1) Programming and data analytics - Introduction to the exciting world of programming, Fun with R, Carrie: Getting started with R•3 minutes, Programming languages, Introduction to R, Intro to RStudio, 2) Programming using RStudio - Programming using RStudio, Programming fundamentals, Operators and calculations, The gift that keeps on giving, Welcome to the tidyverse, Use pipes to nest code, Connor: Coding tips, 3) Working with data in R - Data in R, R data frames, Working with data frames, Cleaning up with the basics, Organizing your data, Transforming data, Same data, different outcome, The bias function, 4) More about visualizations, aesthetics, and annotations - Visualizations in R•2 minutes, Visualization basics in R and tidyverse, Getting started with ggplot, Joseph: Career path to people analytics, Enhancing visualizations in R, Doing more with ggplot, Aesthetics and facets, Annotation layer, Saving your visualizations, 5) Documentation and Reports - Documentation and reports, Overview of R Markdown, Using R Markdown in RStudio, Structure of markdown documents, Meg: Programming is empowering, Code chunks and Exporting documentation.

Enroll today (teams & executives are welcome): http://imp.i384100.net/Py5MLN 

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)

ChatGPT Training: Beginners to Advanced

Colleagues, in the ChatGPT Training: Beginners to Advanced you will be able to upgrade your prompt engineering skills by integrating ChatGPT plugins and ChatGPT APIs to enhance your efficiency. Unlock your potential by crafting your very own chatbot, harnessing the knowledge gained from real-life applications and projects covered in this course, and taking a sneak peek into the future with GPT-4 and ChatGPT Plus. ChatGPT training Course is a smart choice for individuals and organizations looking to enhance their skills and knowledge in the field of language processing and AI. The certification provides a comprehensive understanding of ChatGPT and its capabilities, enabling one to effectively utilize its features for various applications. Additionally, the certification demonstrates an individual's expertise and competence in working with ChatGPT, making them a valuable asset to any organization. Gain high-demand and highly marketable skills in Natural Language Processing, Prompt Engineering, Fine-tuning pre-trained language models, Leveraging ChatGPT for Productivity, Working with ChatGPT and OpenAI API, and Building ChatGPT powered applications. Training lessons include: 1) Introduction to Generative AI, 2) Introduction to ChatGPT and OpenAI, 3) Unleashing the Power of ChatGPT, 4) The Applications of ChatGPT, 5) Human-AI Collaboration and the Future, and 6) Engaging with ChatGPT.

Enroll today (teams & execs welcome): https://fxo.co/IeAu

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)

Foundations: Data, Data, Everywhere (Google)

Colleagues, the Foundations: Data, Data, Everywhere program from Google will enable your organization  to improve its processes, identify opportunities and trends, launch new products, and make thoughtful decisions. You’ll be introduced to the world of data analytics through a hands-on curriculum developed by Google. Current Google Data Analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks using the best tools and resources. Gain an understanding of the practices and processes employed by a junior or associate data analyst in their day-to-day job. - Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox. Learn to Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystems, Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking, Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics and describe the role of a data analyst with specific reference to jobs. Gain high-demand and highly marketable skills including Spreadsheets, Data Analysis, SQL, Data Visualization and Data Cleansing. Training lessons address: 1) Introducing data analytics and analytical thinking - Data analytics in everyday life, Cassie: Dimensions of data analytics, What is the data ecosystem?, How data informs better decisions, Discover data skill sets, Key data analyst skills, All about thinking analytically, Explore core analytical skills, Data drives successful outcomes, Witness data magic; 2) The Wonderful World of Data - Learn about data phases and tools, Stages of the data life cycle, The phases of data analysis and this program, Molly: Example of the data analysis process, Explore data analyst tools; 3) Set Up Your Data Analytics Toolbox - The ins and outs of core data tools, Make spreadsheets your friends, SQL in action, Angie: Everyday struggles when learning new skills, Become a data viz whiz, Lilah: The power of a visualization; and 4) Become a Fair and Impactful Data Professional - The job of a data analyst, Joey: Path to becoming a data analyst, Tony: Supporting careers in data analytics, The power of data in business, Rachel: Data detectives, Understand data and fairness, Alex: Fair and ethical data decisions, Data analysts in different industries and Samah: Interview best practices.

Enroll today (teams & executives are welcome): http://imp.i384100.net/9gK75j 

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)

Generative AI for Everyone

Colleagues, in the Generative AI for Everyone program you will learn what generative AI is and how it works, its common use cases, and what this technology can and cannot do, and How to think through the lifecycle of a generative AI project, from conception to launch, including how to build effective prompts. The potential opportunities and risks that generative AI technologies present to individuals, businesses, and society. Skills you'll gain - Generative AI Tools, Large Language Models, AI strategy, Generative AI and AI Productivity. Instructed by AI pioneer Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI. Andrew will guide you through how generative AI works and what it can (and can’t) do. You’ll get hands-on time with generative AI projects to put your knowledge into action and gain insight into its impact on both business and society. Skill-based lessons include: 1) Introduction to Generative AI - How Generative AI works, LLMs as a thought partner, AI is a general purpose technology, Writing, Reading, Chatting, What LLMs can and cannot do, Tips for prompting, Image generation, 2) Generative AI Projects - Using generative AI in software applications, Trying generative AI code yourself, Lifecycle of a generative AI project, Cost intuition, Retrieval Augmented Generation (RAG), Fine-tuning, Pre-training an LLM, Choosing a model, How LLMs follow instructions: Instruction tuning and RLHF, Tool use and agents, and 3) Generative AI in Business and Society - Day-to-day usage of web UI LLMs, Task analysis of jobs, Additional job analysis examples, New workflows and new opportunities, Teams to build generative AI software, Automation potential across sectors, Concerns about AI, Artificial General Intelligence, Responsible AI, and Building a more intelligent world.

Enroll today (teams & execs welcome): https://imp.i384100.net/9gKrZ4 

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)

Linear Algebra for Machine Learning and Data Science (training)

Colleagues, in the Linear Algebra for Machine Learning and Data Science you will learn to represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, how to apply common vector and matrix algebra operations like dot product, inverse, and determinants, and how ro express certain types of matrix operations as linear transformation, and apply concepts of eigenvalues and eigenvectors to machine learning problems Skills you'll gain include Eigenvalues And Eigenvectors, Linear Equation, Determinants, Machine Learning and Linear Algebra. We also recommend a basic familiarity with Python (loops, functions, if/else statements, lists/dictionaries, importing libraries), as labs use Python and Jupyter Notebooks to demonstrate learning objectives in the environment where they’re most applicable to machine learning and data science. If you are already familiar with the concepts of linear algebra, Course 1 will provide a good review, or you can choose to take Course 2: Calculus for Machine Learning and Data Science and Course 3: Probability and Statistics for Machine Learning and Data Science, of this specialization. A basic familiarity with Python (loops, functions, if/else statements, lists/dictionaries, importing libraries), as labs use Python and Jupyter Notebooks to demonstrate learning objectives in the environment where they’re most applicable to machine learning and data science is recommended. Week 1: Systems of linear equations - Linear Algebra Applied, System of sentences, System of equations, System of equations as lines and planes,, A geometric notion of singularity, Singular vs nonsingular matrices, Linear dependence and independence, The determinant, Week 2: Solving systems of linear equations, Solving non-singular system of linear equations, Solving singular system of linear equations, Solving system of equations with more variables, Matrix row-reduction, Row operations that preserve singularity, The rank of a matrix,, The rank of a matrix in general, Row echelon form, Row echelon form in general, Reduced row echelon form,, The Gaussian Elimination Algorithm, Week 3: Vectors and Linear Transformations - Machine Learning Motivation, Vectors and their properties, Vector operations, The dot product, Geometric Dot Product, Multiplying a matrix by a vector, Matrices as linear transformations, Linear transformations as matrices, Matrix multiplication, The identity matrix, Matrix inverse, Which matrices have an inverse?, Neural networks and matrices, and Week 4: Determinants and c - Singularity and rank of linear transformations, Determinant as an area, Determinant of a product and inverses, Bases in Linear Algebra, Span in Linear Algebra, Eigenbases, Eigenvalues and Eigenvectors, Calculating Eigenvalues and Eigenvectors, On the Number of Eigenvectors, Dimensionality Reduction and Projection, Motivating PCA, Variance and Covariance, Covariance Matrix, PCA - Overview, PCA - Why It Works, PCA - Mathematical Formulation and Discrete Dynamical Systems. 

Enroll today (teams & execs welcome): https://imp.i384100.net/eKmbx6 

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)

AI for Everyone

Colleagues, the AI for Everyone course is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. Learn the meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science, What AI realistically can--and cannot--do, How to spot opportunities to apply AI to problems in your own organization, What it feels like to build machine learning and data science projects, How to work with an AI team and build an AI strategy in your company and How to navigate ethical and societal discussions surrounding AI. Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI. Skill-based lessons include: 1) What is AI? - Machine Learning, What is data?, The terminology of AI, What makes an AI company?, What machine learning can and cannot dos, More examples of what machine learning can and cannot dos, Non-technical explanation of deep learning, 2) Building AI Projects - Workflow of a machine learning project, Workflow of a data science project, Every job function needs to learn how to use data, How to choose an AI project, How to choose an AI project, Working with an AI team, Technical tools for AI teams, 3) Building AI In Your Company - Case study: Smart speaker, Case study: Self-driving car, Example roles of an AI team, AI Transformation Playbook, AI Transformation Playbook, AI pitfalls to avoid, Taking your first step in AI, Survey of major AI application areas, Survey of major AI techniques, and 4) AI and Society - A realistic view of AI, Discrimination/Bias, Adversarial attacks on AI, Adverse uses of AI, AI and developing economies, and AI and jobs.  

Enroll today (teams & execs welcome): https://imp.i384100.net/4P4qr9 

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)

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