From Cover to Code

In this Season 4 finale of From Cover to Code, Angela Andrews and Michael Jenkins close the loop on their journey through *AWS Certified AI Practitioner Study Guide* and finally reveal whether they passed the AWS AIF-C01 exam.

They look back at how well the book aligned to the official AWS exam guide, share what actually helped during their final days of prep, compare testing-center experiences, and talk through what future exam takers should focus on most. The episode also reflects on what it was like to use a book as the backbone of certification prep and sets up what’s next for the podcast.

Whether you are preparing for the AWS Certified AI Practitioner exam yourself or just want a candid debrief on study strategy, exam-day logistics, and lessons learned, this episode brings the season to a strong finish.

Book covered in this season:

• "AWS Certified AI Practitioner Study Guide" by Tom Taulli

Video Chapters:

• 00:00 Did We Pass?
• 03:16 Book Wrap-Up
• 10:01 Study Prep Strategies
• 18:39 Make a Study Plan
• 21:58 Testing Center Experience
• 28:50 The Results Reveal
• 32:06 Key Exam Takeaways
• 42:29 What’s Next: Terraform

Your hosts:

• Angela Andrews - @scooterphoenix
• Michael Jenkins - @managedkaos

Next up:

• "Terraform: Up & Running, Third Edition".

Don’t forget to like, subscribe, and follow along for the next season of From Cover to Code. Join the conversation and share your own certification prep lessons, testing-center experiences, and AWS AI Practitioner takeaways.

#FromCoverToCode #AWS #AIFC01 #AICertification #AWSCertifiedAIPractitioner #GenerativeAI #CloudComputing #Terraform

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

In this episode of From Cover to Code, Angela Andrews and Michael Jenkins shift from chapter review to exam strategy, focusing entirely on how to prepare for and pass the AWS Certified AI Practitioner (AIF-C01) exam.

They break down practical tactics for handling 65 questions in 90 minutes, including when to mark questions for review, why you should never leave an answer blank, and how to use keyword spotting and process of elimination to improve your odds under pressure.

The conversation also covers the realities of exam day, from testing-center mishaps to frustrating at-home proctor experiences, before moving into the exam domains, service scope, and the study resources each host is using to get ready.

Topics covered in this episode:

• Time management strategies for the AIF-C01 exam
• Reading questions carefully and avoiding common traps
• Deciding between at-home testing and an exam center
• Understanding the five AWS AI Practitioner domains
• Study plans, practice exams, and prep resources

Video Chapters:

• 00:00 Episode Intro 
• 01:48 Time Management Tips 
• 04:42 Reading Questions Carefully 
• 06:41 Staying Calm Under Pressure 
• 08:57 Exam Center vs Home Testing 
• 13:42 Core Topics To Know 
• 16:51 Exam Domains Breakdown 
• 19:51 Study Resources And Next Steps

Your hosts:

• Angela Andrews -  @scooterphoenix
• Michael Jenkins -  @managedkaos

If you're preparing for the AWS AI Practitioner exam -- or any certification exam -- this episode gives you a grounded look at both the content areas and the test-day tactics that can make the difference.

#FromCoverToCode #AWS #AIFC01 #AICertification #CloudComputing #GenerativeAI #MachineLearning #AWSCertifiedAIPractitioner

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

In this episode of From Cover to Code, Angela and Michael continue their discussion of the AWS Certified AI Practitioner Study Guide by diving into Chapter 9: Security, Compliance, and Governance for AI Solutions.

What starts with travel reflections and exam prep quickly turns into a practical conversation about what it actually takes to secure AI systems in the real world. The hosts walk through defense in depth, layered AWS security controls, the generative AI security scoping matrix, prompt injection risks, compliance expectations, governance practices, and the AWS services that support each area.

If you're preparing for the AWS Certified AI Practitioner exam or trying to better understand how AI security, compliance, and governance show up in production environments, this episode gives you a strong conceptual walkthrough with plenty of real-world context.

Book chapter covered in this episode:

🔹 Chapter 9: Security, Compliance, and Governance for AI Solutions

Video Chapters:

00:00 Welcome
01:04 Reflections on Ghana and STEM Outreach
04:36 Exam Prep and Final Chapters
06:27 Chapter 9 Overview
09:50 Defense in Depth and Security Layers
19:27 AI Security Scoping Matrix
27:16 Prompt Injection and Zero Trust
34:16 Compliance, Governance, and Quiz Review

Your hosts:

Angela Andrews – @scooterphoenix
Michael Jenkins – @managedkaos

Don’t forget to like, subscribe, and hit the bell so you never miss an episode of From Cover to Code. Join the conversation in the comments and share how you’re approaching AI security, compliance, and governance in your own work.

#FromCoverToCode #AISecurity #AWS #GenerativeAI #AIPractitioner #CloudSecurity #Compliance #Governance

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

In this episode of From Cover to Code, Angela Andrews and Michael Jenkins dig into two essential topics for modern AI practitioners and AWS certification candidates alike: prompt engineering and responsible AI.

They break down what makes a well-designed prompt, why techniques like zero-shot, few-shot, and chain-of-thought matter, and how better prompting leads to better outputs. The conversation then shifts into the ethical and operational side of AI, including toxicity, bias, privacy, intellectual property, model monitoring, and the AWS tools that support responsible AI in practice.

If you're studying for the AWS Certified AI Practitioner exam, this episode is packed with practical takeaways, exam-focused vocabulary, and real-world examples that make the material easier to remember and apply.

Book chapters covered in this episode:

Chapter 7: A Guide to Prompt Engineering
Chapter 8: A Framework for Responsible AI

Video Chapters:

00:00 Welcome and Catch-Up
03:10 Exam Dates and Accountability
07:10 Study Resources and Certification Prep
10:00 Why Prompt Engineering Matters
12:55 Anatomy of a Great Prompt
24:49 Prompting Techniques in Practice
28:49 Prompt Security and Safe AI Use
36:29 Responsible AI Frameworks and AWS Tools
01:11:01 Flashcards, Next Steps, and Wrap-Up

Don’t forget to like, subscribe, and follow From Cover to Code for more conversations on AI, cloud, software development, and certification prep.

#FromCoverToCode #PromptEngineering #ResponsibleAI #AWS #AWSCertifiedAIPractitioner #GenerativeAI #AmazonBedrock #SageMaker

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

In this episode of From Cover to Code, Angela and Michael continue their walk through the AWS Certified AI Practitioner Study Guide with a discussion of Chapters 5 and 6, focused on real-world AWS AI services plus getting started with Amazon Bedrock and Amazon Q.

They break down where services like Rekognition, Comprehend, Kendra, Lex, Polly, Textract, and Fraud Detector fit in real scenarios, then shift into Bedrock's model catalog, playground comparisons, tuning controls, guardrails, and the growing role of Amazon Q inside day-to-day AWS workflows.

Along the way, they work through certification-style quiz questions, unpack model settings like temperature and top P, explore customization concepts like distillation and continued pre-training, and connect AI decisions back to business outcomes, governance, and exam readiness.

Book chapters covered in this episode:

• Chapter 5: Real-World AI Applications with AWS Tools
• Chapter 6: Getting Started with Amazon Bedrock and Amazon Q

Video Chapters:

00:00 Welcome
02:03 Chapters 5 and 6 Overview
04:39 AWS AI Services Overview
19:07 Quiz Review and Exam Prep
25:46 Amazon Q in Practice
29:12 Amazon Bedrock Model Catalog
41:57 Tuning, Guardrails, and Prompting
52:12 AI Metrics, Customization, and Wrap-Up

Your hosts:

• Angela Andrews - @scooterphoenix
• Michael Jenkins - @managedkaos

Don’t forget to like, subscribe, and follow From Cover to Code for more conversations on AI, cloud, software development, certification prep, and real-world tech learning.

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

In this episode of "From Cover to Code", Angela and Michael dive deep into Chapters 3 and 4 of "AWS Certified AI Practitioner (AIF-C01) Study Guide" by Tom Taulli.

What starts as a foundational discussion of AI quickly accelerates into machine learning lifecycles, generative model architectures, transformer mechanics, and the real-world implications of foundation models.

If you’ve ever used ChatGPT, Amazon Q, or Claude and wondered, “What’s actually happening under the hood?” — this episode connects the dots between practical usage and technical foundations.

Chapters covered in this episode:

• Chapter 3: AI and Machine Learning
• Chapter 4: Understanding Generative AI

Expect deep technical breakdowns, exam-ready insights, ethical debates, and live quiz practice to sharpen your AWS AI Practitioner knowledge.

Chapters:

00:00 Welcome & Chapter Reality Check
01:00 The Deep End of AI Foundations
06:00 What AI Really Means (AWS Definition)
10:00 Machine Learning Layers & Data Quality
18:40 The ML Lifecycle & MLOps Framework
26:50 Generative AI Models Explained (GANs, VAEs, Transformers, Diffusion)
37:50 Ethics, Copyright & Hallucinations
51:55 Quiz Practice & Exam Strategy



Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

The Journey to Certification: AWS AI Practitioner

We’re back for a brand-new season of From Cover to Code 📘💻 — and this time, we’re diving into AI on AWS.

In this Season 4 premiere, Michael Jenkins and Angela Andrews kick off their review of the "AWS Certified AI Practitioner (AIF-C01) Study Guide" by Tom Taulli.

This episode sets the foundation for the entire season, focusing on *why* the AWS AI Practitioner certification exists, *who* it’s designed for, and the AWS fundamentals every AI practitioner is expected to understand before touching models, prompts, or GenAI tools.

If you’re cert-curious, career-pivoting, or trying to cut through the AI hype with real cloud knowledge, this episode lays the groundwork for your certification journey—and invites you to take it alongside us.

In this episode, we cover:

• Why AWS introduced the AI Practitioner certification
• How AWS frames AI, machine learning, and generative AI at a foundational level
• Core AWS services and cloud concepts tested on the exam
• Exam structure, scoring, and certification tiers
• Why scheduling your exam date makes studying *real*
• How to use this book—and this series—as a practical study companion
• Tools and strategies to study smarter, not harder

Read along, join us live, and let’s go **from cover → to code → to certification**, together.

Book & Resources

• The book: [https://www.oreilly.com/library/view/aws-certified-ai/9798341622326/](https://www.oreilly.com/library/view/aws-certified-ai/9798341622326/)
• AWS Free Tier [https://aws.amazon.com/free/](https://aws.amazon.com/free/)
• Google NotebookLM (study tool mentioned [https://notebooklm.google.com/](https://notebooklm.google.com/)

Video Chapters

00:00 Welcome to From Cover to Code
01:09 Season 4 Kickoff and Host Catch-Up
05:50 Why AWS AI Practitioner Certification
08:26 Scheduling the Exam Makes It Real
11:52 Exam Structure, Scoring, and Weighting
18:46 AWS Certification Levels Explained
27:03 Cloud Computing and AWS Fundamentals
34:27 Core AWS Services Every Practitioner Should Know
37:36 AWS Glue, ETL, and Real-World Case Study
42:49 Live Quiz and Exam Mindset
59:00 What’s Next: AI, ML, and Generative AI

Don’t forget to like, subscribe, and hit the bell so you never miss an episode of From Cover to Code.

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

From Cover to Code — S3E6: Next-Level DevOps with Python

In this Season 3 finale, Angela and Michael close out "Hands-On Python for DevOps" with an in-depth conversation about Chapter 13 — "The Tools to Take Your DevOps to the Next Level". They explore advanced automation techniques, real-world monitoring strategies, and modern troubleshooting workflows that help teams scale their DevOps practices with confidence.

The hosts dig into step functions, observability stacks, event-driven operations, and the growing role of AI tools that support high-velocity engineering teams. They also reflect on the biggest lessons from this season — from infrastructure automation to MLOps — and how the themes of the book connect to their day-to-day work as practitioners and creators.

Beyond the chapter, Angela and Michael share updates on AfroTech, community highlights, upcoming podcast projects, and the exciting future of "From Cover to Code" as they prepare for Season 4.

The book: https://www.oreilly.com/library/view/hands-on-python-for/9781835081167/B21320_01.xhtml
The code: https://github.com/PacktPublishing/Hands-On-Python-for-DevOps/tree/main

Video Chapters:

00:00 Welcome & Opening Banter
01:00 Wrapping Up the Book
05:18 Chapter 13: Advanced Automation Tools
11:29 Monitoring with Grafana & Prometheus
14:48 Troubleshooting & Event Response Strategies
26:14 AfroTech Recap
32:54 Connecting with other Black Tech Creators on https://blktechplus.com/
36:40 Expanding to Spotify
43:00 Looking Ahead to Season 4

Your Hosts:
Angela Andrews – @scooterphoenix
Michael Jenkins – @managedkaos

Don’t forget to like, subscribe, and join the conversation! Share your takeaways from this season and let us know what books you’d love to see in Season 4.



Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

Angela Andrews and Michael Jenkins continue their journey through *Hands-On Python for DevOps* with a deep dive into Chapters 11 and 12 — exploring how Python bridges the gap between data science, operations, and infrastructure management.

This episode connects the dots between MLOps, DataOps, and Infrastructure as Code (IaC) — showing how Python’s simplicity and versatility make it an essential tool for automating data workflows, deploying machine learning models, and defining infrastructure reproducibly.

Expect lively discussion, insightful quotes, and practical takeaways from real-world DevOps experience.

Book Chapters Covered

- Chapter 11: MLOps and DataOps
- Chapter 12: Python and Infrastructure as Code (IaC)

Video & Podcast Chapters

00:00 Welcome and Episode Setup
03:00 The Future Is Now – AI and Career Differentiation
06:30 Why Python Dominates DataOps and MLOps
10:45 Working with Data and the Power of Pandas
14:15 The Three V’s of Data Complexity: Velocity, Volume & Variety
19:30 Streaming Data and Real-Time Processing with Flink and Pandas
25:00 AI Evolution and How Tech Books Keep Up
32:30 Understanding Infrastructure as Code (IaC)
36:00 Salt vs Ansible vs Terraform SDK – Python in IaC Tools
43:30 Community Shout-Outs and Next Episode Preview

Key Takeaways

- Python is the universal connector between DevOps, DataOps, and MLOps — powering automation, analytics, and infrastructure.
- The Three V’s (Velocity, Volume, Variety) define modern data challenges; Python libraries like Pandas and Flink help manage them efficiently.
- Infrastructure as Code (IaC) transforms how teams manage cloud resources — codifying provisioning, replication, and scaling for AWS, Azure, and GCP.
- Tools like Terraform + Ansible deliver the perfect one-two punch for deployment and configuration.
- Even as AI-assisted coding evolves, foundational knowledge still matters. Understanding the “nuts and bolts” ensures better troubleshooting and design.
- The hosts reflect on enduring classics like "UNIX in a Nutshell" and discuss how agile digital publishing keeps technical learning relevant.

🔗 Resource Links

📘 The Book — "Hands-On Python for DevOps" 

💻 The Code Repository: PacktPublishing/Hands-On-Python-for-DevOps

Conferences:

• BITCon
• Afrotech
• RenderATL

🙌 Join the Conversation

Don’t forget to like, subscribe, and comment to share your own experiences with Python, MLOps, and IaC.

Follow the hashtag #CoverToCode on LinkedIn and YouTube to catch upcoming discussions — next up: “The Tools to Take Your DevOps to the Next Level.”

Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​

Angela and Michael are back with another deep dive into Hands-On Python for DevOps!
In this episode, they explore Chapters 9 and 10 — Using Python for CI/CD Pipelines and Common DevOps Use Cases in Big Companies.

They unpack how Python streamlines continuous integration and delivery, making pipelines faster, more reliable, and easier to maintain. Then, they look at how major organizations apply DevOps and automation principles at scale — from Samsung’s data platform overhaul to MLB’s pitch-clock innovation — and what we can all learn from those approaches.

Expect 🔥 insights, practical pipeline breakdowns, and lively discussion from two DevOps practitioners who live and breathe this stuff.

Book chapters covered in this episode
🔹 Chapter 9: Using Python for CI/CD Pipelines
🔹 Chapter 10: Common DevOps Use Cases in Big Companies

Video Chapters
00:00 Welcome & Opening Banter
02:45 Setting the Stage – Chapters 9 & 10 Overview
06:30 Why CI/CD Is Missing from Most Formal Education
09:35 The Doug Philosophy – “Do More and You’ll Learn More”
17:20 Michael’s 7-Step CI/CD Pipeline Breakdown
23:00 Tools of the Trade – Linting, Testing, and Packaging in Python
29:00 Deployment Rollbacks and Blue-Green Strategies
33:00 Business Use Cases: Samsung, Intertek, and Major League Baseball
48:10 Reflections, Lessons Learned & What’s Next (MLOps + IaC Preview)
51:00 Angela’s Terraform Tech Talk & Closing Thoughts

Resources
📘 The book: https://www.oreilly.com/library/view/hands-on-python-for/9781835081167/B21320_01.xhtml
💻 The code repository: https://github.com/PacktPublishing/Hands-On-Python-for-DevOps/tree/main
🧪 The demo from this episode: https://docs.google.com/presentation/d/1ci087ShNepkFJLO1GvshIXO8TuMD5_E-dcKlnJu4BR8/edit?usp=sharing

Don’t forget to like, subscribe, and hit the bell so you never miss an episode of From Cover to Code!
Join the conversation in the comments; we want to hear how you’re using Python in your own CI/CD pipelines.


Find us online at covertocode.com.

Hosted by:

• Angela A.  @scooterphoenix 
• Michael J.  @managedkaos ​