Introduction to Data Engineering (IBM)

Colleagues, the “Introduction to Data Engineering” program from IBM will jumpstart your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem. You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field. Next you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will become familiar with the components of a data platform and gain an understanding of several different types of data repositories such as Relational (RDBMS) and NoSQL databases, Data Warehouses, Data Marts, Data Lakes and Data Lakehouses. You’ll then learn about Big Data processing tools like Apache Hadoop and Spark. You will also become familiar with ETL, ELT, Data Pipelines and Data Integration. This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. You will also learn about security, governance, and compliance. You will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. You will hear from several experienced Data Engineers, sharing their insights and advice. By the end of this course, you will also have completed several hands-on labs and worked with a relational database, loaded data into the database, and performed some basic querying operations

Enroll today (teams & executives are welcome): imp.i384100.net/Jz3B9R 

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)

Much career success, Lawrence E. Wilson - AI Academy (share with your team) https://tinyurl.com/hh7bf4m9 

Certified Prompt Engineering Expert (CPEE)™

Colleagues, in the “Certified Prompt Engineering Expert (CPEE)™” program you will develop an in-depth understanding of Large Language Models and prompt engineering techniques, gain practical experience in using OpenAI API and implementing API calls for interacting with LLMs, and master advanced techniques for prompt engineering to effectively guide LLMs and generate the desired outputs. Gain an Introduction to Large Language Models, the fundamentals of prompting, patterns and techniques for prompt engineering, API calls with OpenAI API, GPT-4 extensions and their practical use cases, advanced prompt engineering and patterns for complex tasks and the future of advanced prompt patterns, AI and LLMs. And acquire prompt engineering skills involving interaction with large language models, building new applications and projects utilizing the power of LLMs, studying the potential and capabilities of using prompt patterns, discovering the latest industry trends and skills required for using LLMs in different applications, enhancing your career and business by creating complex prompt-based applications, and fuel your curiosity about the advancement in AI, the future of LLMs, and their use cases. Skill-based lessons address: 1) Introduction to Large Language Models, 2) Prompt Engineering Fundamentals, 3) Prompt Engineering Techniques, 4) Using the OpenAI API, 5) Advanced Prompt Engineering, 6) Use Cases and Demonstrations, 7) ChatGPT Plugins, 8) Ethics, Limitations, and Future of LLMs, and 9) Certification Exam.

Enroll today (teams & executives are welcome): https://tinyurl.com/564tx2w7 

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

“Transformative Innovation” book series for your listening-reading pleasure: 

 

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) 

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

IBM Data Analyst Professional Certificate

Colleagues, the “IBM Data Analyst Professional Certificate” program will prepare for a career as a data analyst. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required. Master the most up-to-date practical skills and tools that data analysts use in their daily roles. Learn how to visualize data and present findings using various charts in Excel spreadsheets and BI tools like IBM Cognos Analytics & Tableau. Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services. Gain technical experience through hands on labs and projects and build a portfolio to showcase your work. You’ll learn the latest skills and tools used by professional data analysts including Excel spreadsheets, Python, Pandas, Numpy, Jupyter Notebooks, Cognos Analytics, and more. You’ll work with a variety of data sources and project scenarios to gain practical experience with data manipulation and applying analytical skills. You'll also have the option to learn how generative AI tools and techniques are used in data analysis. You’ll earn an IBM Digital badge and gain access to career resources to help you in your job search. This program is ACE® and FIBAA recommended—when you complete, you can earn up to 12 college credits and 6 ECTS credits. Skill-based lessons include: 1) Introduction to Data Analytics, 2) Excel Basics for Data Analysis, 3) Data Visualization and Dashboards with Excel and Cognos, 4) Python for Data Science, AI & Development, 5) Python Project for Data Science, 6) Databases and SQL for Data Science with Python, 7) Data Analysis with Python, 8) Data Visualization with Python, 9) IBM Data Analyst Capstone Project, 10) Generative AI: Enhance your Data Analytics Career, and 11) Data Analyst Career Guide and Interview Preparation.

Enroll today (teams & executives are welcome): https://imp.i384100.net/EKn2kP 

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)

Much career success, Lawrence E. Wilson - AI Academy (share with your team) https://tinyurl.com/hh7bf4m9 

Introduction to Deep Learning in Python

Colleagues, in the “Introduction to Deep Learning in Python” program you will learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python. This course is part of several machine learning and deep learning tracks, offering you clear pathways to build your skills and experience in this area once you’ve completed the introductory course, whether you want to complete a personal project or move towards a career as a Machine Learning Scientist. Skill-based training lessons include: 1) Basics of deep learning and neural networks - become familiar with the fundamental concepts and terminology used in deep learning, and understand why deep learning techniques are so powerful today. You'll build simple neural networks and generate predictions with them, 2) Building deep learning models with keras - use the Keras library to build deep learning models for both regression and classification. You'll learn about the Specify-Compile-Fit workflow that you can use to make predictions, and by the end of the chapter, you'll have all the tools necessary to build deep neural networks, 3) Optimizing a neural network with backward propagation - optimize the predictions generated by your neural networks. You'll use a method called backward propagation, which is one of the most important techniques in deep learning. Understanding how it works will give you a strong foundation to build on in the second half of the course, and 4) Fine-tuning keras models - optimize your deep learning models in Keras. Start by learning how to validate your models, then understand the concept of model capacity, and finally, experiment with wider and deeper networks.

Enroll today (teams & executives are welcome): https://datacamp.pxf.io/QyqGP3 

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)

Data Science A-Z: Hands-On Exercises & ChatGPT Prize

DS colleagues, in the “Data Science A-Z: Hands-On Exercises & ChatGPT Prize” program you will learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization plus How to perform all steps in a complex Data Science project, create Basic Tableau Visualisations, perform Data Mining in Tableau, understand how to apply the Chi-Squared statistical test, apply Ordinary Least Squares method to Create Linear Regressions, assess R-Squared for all types of models, analyze the Adjusted R-Squared for all types of models, create a Simple Linear Regression (SLR), a Multiple Linear Regression (MLR) and much more. 28 sections • 217 lectures • 21h 13m total length. Skill-based training lessons include: 1) What is Data Science?, 2) Visualisation - Introduction to Tableau, How to use Tableau for Data Mining, Advanced Data Mining With Tableau, 3) Modeling - Stats Refresher, Simple Linear Regression, Multiple Linear Regression, 4) Logistic Regression, 5) Building a robust geodemographic segmentation model, 6) Assessing your model, Drawing insights from your model, Model maintenance, 7) Data Preparation - Business Intelligence (BI) Tools, ETL Phase 1: Data Wrangling before the Load, ETL Phase 2: Step-by-step guide to uploading data using SSIS, Handling errors during ETL (Phases 1 & 2), SQL Programming for Data Science, ETL Phase 3: Data Wrangling after the load, Handling errors during ETL (Phase 3), and 8) Communication - Working with people, Presenting for Data Scientists, and Homework Solutions. 

Enroll today (teams & executives are welcome): https://tinyurl.com/4eavzjh2 

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)

Much career success, Lawrence E. Wilson - AI Academy (share with your team) https://tinyurl.com/hh7bf4m9 

Prompt Engineering Specialization

Colleagues, in the “Prompt Engineering Specialization” you will become a Prompt Engineering Expert. Master prompt engineering patterns, techniques, and approaches to effectively leverage Generative AI. Learn in-demand skills from university and industry experts. Master a subject or tool with hands-on projects. Develop a deep understanding of key concepts. Earn a career certificate from Vanderbilt University. By the end of the specialization, you will be able to use prompts and conversations with ChatGPT to accomplish amazing feats such as: writing and outlining 10X faster, brainstorming new ways of solving problems, planning complex events, trips, processes, etc., automatically generating PowerPoint presentations and visualizations from Excel data, extracting key information from PDFs and documents, and producing marketing content from transcripts and videos or that are personalized for specific customers. Applied Learning Project - tap into emergent reasoning capabilities using personas to producing social media posts with Generative AI. Each course includes multiple hands-on prompt engineering exercises that will incrementally build your prompt engineering skills.Training lessons include: 1) Prompt Engineering for ChatGPT, 2) Introduction to Prompts, 3) Prompt Patterns, 4) Few-Short Examples, 5) Prompt Patterns I, II and III, 6) ChatGPT Advanced Data Analysis, 7) Introduction to ChatGPT Advanced Data Analysis, 8) Introduction to ChatGPT Advanced Data Analysis Use Cases, 9) Tackle the Right Problems: Appropriate Use of ChatGPT Advanced Data Analysis, 10) Human and AI Process Planning in ChatGPT Advanced Data Analysis, 11) Error Identification Techniques, Error Handling, and Techniques for Large Documents & Outputs, and 12) Trustworthy Generative AI. 

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

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)

Master the Power BI Basics and Data Visualization

Colleagues, in the “Master the Power BI Basics and Data Visualization” program you’ll gain a 360° overview of the Power BI basics and learn how to use the tool to build impactful reports. In this course, you’ll go from zero to hero as you discover how to use this popular business intelligence platform through hands-on exercises. Before diving into creating visualizations using Power BI's drag-and-drop functionality, you’ll first learn how to confidently load and transform data using Power Query and the importance of data models. You’ll also learn to drill down into reports and make your reports fully interactive. You’ll start by looking at some of the fundamentals of Power BI, getting to grips with Data, Model, and Report views. You’ll learn to load data sets, build a data model, and discover how to shape and transform your data with Power Query Editor. As you progress through the course, you’ll have access to hands-on exercises that can hone your skills. You’ll look at various visualizations, sort different data types, and learn to drill deeper into your reports. Create Powerful Data Visualizations. Skill-based training modules include: 1) Getting Started with Power BI - Discover how to navigate this intuitive tool and get to grips with Power BI’s Data, Model, and Report views. You’ll load multiple datasets in the Data view, build a data model to understand the relationships between your tables in Model view, and create your first bar graph and interactive map visualization in Report view. You’ll also practice using Power Query Editor to prep your data for analysis, 2) Visualizing Data - Through hands-on exercises, you’ll learn how to change and format a wide range of visualizations, before moving on to sorting data and creating hierarchies—making it possible for you to drill into your reports, 3) Transforming Data - Learn how to shape and transform your data before the data analysis using Power Query Editor, and 4) Filtering - Discover how to filter the information in your reports by location and control how these filters interconnect and interact with other visuals in your report.

Enroll today (teams & executives are welcome): https://datacamp.pxf.io/PyLyrM 

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)

Much career success, Lawrence E. Wilson - AI Academy (share with your team) https://tinyurl.com/hh7bf4m9