APC Mastery Path

🚀 Automate your Power BI reports documentation using AI tools. Yes, you have read it correctly, it is not a clickbait!   This post is to showcase my latest video which explores how TMDL (Tabular Model Definition Language) can transform the way we document Power BI reports. As someone deeply involved in construction analytics, I've always sought ways to make our documentation processes more efficient and reliable.   Imagine being able to extract your entire Power BI model - every relationship, measure, and table structure - and having AI automatically generate comprehensive documentation. This isn't science fiction; it's achievable through the power of TMDL files and AI integration.   In this comprehensive guide, I walk you through: 🔍 Understanding TMDL fundamentals ⚙️ Setting up the perfect tech stack with Power BI and VSCode 📊 Exporting Power BI projects as TMDL files 🤖 Leveraging AI tools for automated documentation 📚 Real-world applications in construction analytics   Check out the full tutorial here: https://lnkd.in/eQ82ngWf   Let's connect and discuss how we can leverage these tools to transform construction analytics! Drop your thoughts below 👇   This tutorial is part of our broader mission at APC Mastery Path, where we're dedicated to supporting RICS APC candidates while exploring innovative AI implementations in construction. Whether you're preparing for your RICS chartership or looking to enhance your data analytics capabilities, this video provides practical insights you can implement immediately.     #PowerBI #AIInnovation #ConstructionTech #DataAnalytics #RICS #APCMasteryPath #Innovation #ConstructionIndustry #DataAutomation #BusinessIntelligence

Week 2 - 2025 Update:   📊 Just released another construction data analytics tutorial , focusing on a common challenge in our industry: messy construction data.   In this tutorial, I demonstrate how to transform and consolidate datasets with inconsistent formats - a frequent headache in construction firms. Using Power Query and Power Pivot in Excel, I walk through practical solutions for handling different delimiters, varied date formats, inconsistent column names, and non-standardized payment status terminology.   🖥️Tech stack: Excel, Power Query & Power Pivot   ⌚Time investment required: 15 minutes   📽️You can watch the video from the following link: https://lnkd.in/er2wUsen   🏫As part of my commitment to promoting open knowledge sharing in the UK construction sector, all example files are available in my GitHub repository. Whether you're a quantity surveyor, cost manager, or construction professional looking to enhance your data analytics capabilities, this step-by-step guide will help you implement these solutions in your daily work.   Let's continue building a more data-driven construction industry, one tutorial at a time.   You can find below the links to my previous videos in this series.   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/e7Kf2_Y5 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the code and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/eQG69w7Y ⚫Transform Hierarchy to Database in MS Power Query using Custom Columns and Group By - https://lnkd.in/ei-qciJC ⚫Transform Hierarchy to Database in MS Excel using Nested Ifs, IFS & SWITCH - https://lnkd.in/e2bzpWNR     #ConstructionAnalytics #DataTransformation #PowerQuery #ConstructionIndustry #PowerPivot #MSExcel #DataAnalytics

🚀 Excited to share my latest project: An innovative app that streamlines the creation of training data for LLM fine-tuning!   🎯 The Challenge: Converting organizational documents into Q&A pairs for LLM fine-tuning is traditionally a time-consuming process. Plus, using cloud services for sensitive data isn't always ideal. That's why I built this local solution!   💡 Introducing the MarkItDown Converter: A Streamlit-based app that efficiently converts: • PDFs • Office files • Images → Into markdown and CSV formats for Unsloth fine-tuning   🛠️ Tech Stack: • Streamlit for the intuitive frontend • Ollama for local LLM processing • Python for robust backend operations   🔍 Key Features: ✨ Three powerful conversion paths: 1. Files → Markdown 2. Markdown → CSV 3. Direct Files → CSV conversion   🎥 I've created a detailed tutorial video showcasing the app in action: https://lnkd.in/e9qTq-yC   ⚙️ Want to try it yourself? Just follow these 8 simple steps [detailed in the first comment]   📚 Perfect for: • Organizations needing to fine-tune LLMs • Teams handling sensitive data • Anyone looking to automate Q&A pair generation   🌐 Get started with the app: https://lnkd.in/e3HvJ9BH   🏗️ At APC Mastery Path, we're passionate about bridging AI and construction. We provide specialized RICS APC mentoring packages and showcase practical AI implementations in construction.   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/e7Kf2_Y5 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the code and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/eQG69w7Y   📲 Let’s connect! Follow along for more insights into AI development, the APC journey, and LLM customization. Together, we’ll unlock the full potential of AI on our local systems!     #ArtificialIntelligence #LLM #Streamlit #Python #DataScience #RICS #APCMasteryPath #ConstructionTech #Innovation #OpenSource #AI #DataAnalytics #ConstructionIndustry #Unsloth #MarkitDown #Ollama # MarkitDown

🔄 Following up on my previous post about hierarchical data transformation in Excel, I'm excited to share a more automated approach using Power Query! In this comprehensive video tutorial , I demonstrate how to transform complex hierarchical data structures into analysis-ready databases using Power Query. The tutorial breaks down the process into three main stages:  ✨Understanding header levels within your data structure,  🎯Implementing strategic column splits, and  🔄Utilizing fill-down operations to maintain data integrity. For those working with regularly updated datasets, you'll also discover a bonus Power Query trick that significantly streamlines the refresh process. 📽️You can watch the video from the following link : https://lnkd.in/ekxeTX9r While Excel formulas can handle this task effectively, Power Query offers enhanced capabilities for repeatable data transformations, especially when dealing with large datasets that require frequent updates. The solution presented combines custom column creation with group by operations to create a robust, maintainable data transformation process. This approach is particularly relevant to our ongoing discussion about construction data analytics maturity. As many of us in the industry recognize, the current state of construction data often requires significant preparation before we can implement advanced analytics or AI solutions. It's crucial to acknowledge that establishing robust data transformation processes is a fundamental step toward digital transformation. Through the Construction Data Analytics Initiative, we're advocating for a measured, practical approach to digital advancement. While AI presents exciting possibilities, our immediate focus should be on building strong data foundations. As the saying goes, we need to walk before we can run – and mastering tools like Power Query, Power BI and advanced Excel helps us take those essential first steps. Drop your data challenges in the comments or DM me. Every week, we'll tackle a new problem and share the solution with our growing community.   Who's with me on this data analytics journey? 🚀   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/eSxVAzA3 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the files and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/ewyq-NCS ⚫Previous Excel tutorial: https://lnkd.in/enQygRfZ #ConstructionAnalytics #DataTransformation #PowerQuery #DigitalConstruction #ConstructionInnovation #BusinessIntelligence #DataScience #PowerBI #ExcelTips #DataAnalytics #RICS #DatabaseManagement #DataCleaning #ExcelTutorial #ExcelForConstruction #ConstructionIndustry #DigitalTransformation #DataDriven #BuildingAnalytics #DataStrategy #DataArchitecture #BusinessEfficiency #ProcessAutomation #DataManagement #ConstructionTechnology #DigitalSkills

Linkedin Post:   🏗️ Excited to launch "Construction Data Analytics" - a weekly initiative sharing real-world data challenges and solutions in the construction industry!   This week's challenge: Transforming messy hierarchical data into a clean database format using Excel functions. While this might be basic for financial analysts, I noticed a significant gap in construction-specific data analytics content online. Most tutorials focus on financial data, but construction data comes with its own unique challenges!   In this video, I break down: ✨ Header level detection with LEN & SUBSTITUTE 🎯 Smart implementations of nested IF statements ⚡ Advanced SWITCH and IFS formulas 🔄 Automated fill-down techniques   📽️You can watch the video from the following link : https://lnkd.in/e2bzpWNR   🤝 Here's where it gets interesting: I'm inviting fellow construction professionals to join this journey! Got a data challenge that's been bugging you? Let's tackle it collaboratively! Together, we can explore innovative solutions and bridge the tech gap in our industry.   I'm continuously learning and experimenting with Excel, Power BI, Power Query, and exploring AI applications in construction. Let's learn and grow together!   Drop your data challenges in the comments or DM me. Every week, we'll tackle a new problem and share the solution with our growing community.   Who's with me on this data analytics journey? 🚀   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/e7Kf2_Y5 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the files and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/eQG69w7Y   #ConstructionDataAnalytics #ConstructionTech #DataAnalytics #Excel #PowerBI #Innovation #Construction #DataTransformation #ContinuousLearning #ConstructionIndustry

🚀 Overcoming Challenges with Open WebUI & Ollama: Bringing Local AI to Life!   I recently faced a challenge that inspired my latest YouTube tutorial.I ran into a problem where I could not upload my GGUF finetuned models to Open WebUI. I needed a way to export custom models to Ollama for direct use with Open WebUI. Instead of letting that stop me, I developed a step-by-step video to help others set up a seamless environment for local AI interactions!   Curious about running powerful Large Language Models (LLMs) on your machine, with no reliance on the cloud? This tutorial shows how to make the best use of Open WebUI, combined with Ollama, to chat with AI models offline and even customize their personalities.   📽️ You can watch the video from the following link: Local AI Chat with Open WebUI & Ollama + Export Finetuned models to Ollama https://lnkd.in/eTHYA8jS    What’s Covered in the Video: ⚫Python Installation to lay the groundwork for an effective AI environment. ⚫Setting Up Ollama: I demonstrate how to install Ollama and chat with LLMs directly in the terminal. ⚫Installing and Using Open WebUI: Learn how to download Open WebUI from GitHub and use it as a friendly interface for interacting with AI models. ⚫Exporting Customized Models to Ollama: I walk through the process of creating and exporting fine-tuned models to Ollama, adding unique personalities and capabilities to suit specific tasks. ⚫GitHub Repositories & Resources: A look at the essential resources to deepen your understanding and explore further.   🌐 Why Watch? By the end, you'll know how to: ⚫ Seamlessly integrate and chat with LLMs on Open WebUI for your workflow. ⚫Customize AI models for specific tasks, right on your desktop. ⚫ Maximize your local AI setup with practical insights into model fine-tuning.   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/e7Kf2_Y5 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the code and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/eQG69w7Y   📲 Let’s connect! Follow along for more insights into AI development, the APC journey, and LLM customization. Together, we’ll unlock the full potential of AI on our local systems!   #OpenWebUI #Ollama #LocalAI #LargeLanguageModels #PythonAI #LLMChat #AILocalSetup #APCMasteryPath #AIChatBot #ModelFile #APCTips #TechTutorial

🎉 From PDFs to Podcasts: The Final Step in Our Open-Source LLM Series! 🎉   After a transformative journey across 4 pillars, we’re finally bringing text to life! In Part 4: Converting Text to Speech, I’ll show you how to use open-source models Bark and Parler to transform refined transcripts into immersive audio—completing the conversion from PDF to podcast! 📄➡️🎙️   In this final video, we’ll: - Test both TTS models with trial outputs - Process our cleaned transcript file from Pillar 3 - Combine audio arrays into a polished podcast-ready file   📺You can watch the video from the following link - Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 4 - https://lnkd.in/ehTyiUVh   💻 Get the Full Code & Resources: Access everything on my GitHub repository (https://lnkd.in/e5Mx9pSW) and explore the Meta Llama Recipes for even more customization. This series is all about making advanced AI tools accessible for content creation enthusiasts and AI learners alike!   📽️You can watch all the previous video related to this series from the links below: ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 4 : https://lnkd.in/ehZ9B-Fs ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 3: https://lnkd.in/eEVZKwdq ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 2: https://lnkd.in/etiMZENM ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 1: https://lnkd.in/edyCp7Sb     🌐 For more tutorials and insights, check out APC Mastery Path (https://lnkd.in/e6FMCxkf).   Catch up on the series and join me for the finale! Don’t forget to like, subscribe, and share if you’re ready to dive into AI-driven podcasting!   #PDFtoPodcast #OpenSourceLLM #AIforAudio #APCMasteryPath #TextToSpeech #PodcastAutomation #BarkModel #ParlerTTS #Llama3.1

🎙️ Convert PDFs to Podcasts with Open-Source LLMs! Part 3: Refining the Transcript 🎙️   The journey continues! 🚀 In this third instalment of our series, we're tackling Pillar 3: Refining the Transcript—a pivotal step that transforms a basic transcript into a polished, conversation-style script with emotions and character.   In this video, I show you how to use Llama 3.1 8b Instruct to refine our initial transcript draft into a structured dialogue between two speakers, complete with assigned emotions and sentence flow. By the end, you’ll have a refined transcript saved as a PICKLE file, bringing us closer to the final stage: converting this into audio! 🎧   📽️You can watch the video from the following link: https://lnkd.in/ehZ9B-Fs   💻 Full Project Code Available: Want to try this yourself? Access all the code and produced outputs on my [GitHub repository](https://lnkd.in/e5Mx9pSW). I’ve also included a link to the Meta Llama Recipes GitHub for those looking to explore even further. This is a hands-on, open-source adventure into AI-driven podcast creation!   🌐 Catch Up on Previous Videos: Missed the earlier steps? No worries! We’re building this project one pillar at a time: 1. 📄PDF Loading & Preprocessing 2. ✍️ Writing the Transcript 3. 🤖 Refining the Transcript (today’s focus) 4. 🎙️ Converting Text to Speech   📽️You can also watch the videos covering the previous steps from the links below: ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 3: https://lnkd.in/eEVZKwdq ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 2: https://lnkd.in/etiMZENM ⚫Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 1: https://lnkd.in/edyCp7Sb   🔗 Visit my website: [APC Mastery Path](https://lnkd.in/e6FMCxkf) for additional resources, tutorials, and insights on AI in content creation, construction, and analytics.   Join me in this exciting journey as we bring text to life, one step at a time. Don’t forget to **like, subscribe**, and share if you’re finding this series helpful. Let’s unlock the power of AI for audio content together!   #PDFtoPodcast #OpenSourceLLM #AIforAudio #APCMasteryPath #TranscriptRefinement #PodcastAutomation #Llama3.1

🎙️ From PDFs to Podcasts with Open-Source LLMs – Pillar 2 of Our Series! 🎙️   Welcome back to our groundbreaking journey! 🚀 In our third video of this series, we’re delving into Pillar 2: Writing the Transcript—a crucial step that turns raw, cleansed text into a conversation-ready script. Using Llama 3.1 8b Instruct, I’ll show you how to set up an effective system prompt to craft a first iteration transcript that feels alive, with two speakers, dedicated sentences, and emotional depth.   In this episode, I guide you step-by-step on building a dynamic, conversation-style transcript. This is where your PDF truly begins its transformation into audio content! 🎧 Ready to see how AI can create a conversation from text?   📽️You can watch the video from the following link: https://lnkd.in/eEVZKwdq     🛠️ Full Code & Resources: All project code and outputs are available on my [GitHub repository](https://lnkd.in/e5Mx9pSW). You’ll also find the Meta Llama Recipes GitHub repository linked for those interested in deeper customization. Let’s make AI accessible, one step at a time!   🌐 Missed Videos 1 & 2 for the first Pillar? Don’t worry! Catch up and join us for each part as we move through the 4 Pillars of creating AI-driven podcasts: 1. 📄 PDF Loading & Preprocessing 2. ✍️ Writing the Transcript (today’s focus) 3. 🤖 Refining the Transcript 4. 🎙️ Converting Text to Speech   You can watch the videos for Pillar one from the links below: 🟣Pillar 1 - PDF loading and Preprocessing - Part 1 : https://lnkd.in/ehiggj3w 🟣Pillar 1 - PDF loading and Preprocessing - Part 2 : https://lnkd.in/ePfgdbRD     🔗 Visit my website: [APC Mastery Path](https://lnkd.in/e6FMCxkf) for more insights, resources, and tutorials as we unlock the power of AI in content creation, construction, and analytics.   Whether you're here to learn, build, or explore AI’s potential, join us in this series! Let’s make tech work for us—turning text into talk, one step at a time. Don’t forget to like, subscribe, and share if you’re as excited about this journey as we are!   #PDFtoPodcast #AITransformation #OpenSourceLLM #AIforAudio #APCMasteryPath #PodcastAutomation #AIContentCreation #Llama3.1

🎙️ Turn PDFs into Podcasts with Open-Source LLMs! Part 2 of Pillar 1 🎙️   Exciting times ahead as we dive further into the art of transforming PDFs into audio podcasts! In this episode, I’m covering the second and final part of Pillar 1: PDF Loading and Preprocessing**. Using **Llama 3.1, I’ll demonstrate how to cleanse raw text by removing extra spaces, page numbers, and irrelevant data, preparing it for a seamless transition to Pillar 2: Writing the Transcript.   📽️You can watch the video for the second part of Pillar through this link: Convert PDFs to Podcasts - Open Source alternative with Llama 3.1 , Parler TTS & Bark - Part 2 : https://lnkd.in/eYnyXXGB    🔗 Get Hands-On: Full project code and resources are available on my Github page https://lnkd.in/e5Mx9pSW , along with the Meta Llama Recipes GitHub repository for additional support. These resources are tailored for those ready to explore AI-powered podcast creation!   🌐 Explore More: Visit my youtube channel APC Mastery - https://lnkd.in/e5T-BKdg for in-depth tutorials and insights on AI applications in construction and data analytics.   Let’s take text transformation to the next level with AI! Don’t forget to like, share, and subscribe if you’re following along on this journey to audio automation. 📈   #PDFtoPodcast #OpenSourceLLM #AIforAudio #APCMasteryPath #TextProcessing #PodcastAutomation #Llama3.1