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Here are YouTube channels to learn Excel, Power BI & SQL: 1. EXCEL - MyOnlineTrainingHub - Leila Gharani 2. POWER BI - Guy in a Cube - Avi Singh 3. SQL - Programming with Mosh - Kevin Stratvert Who else belongs on this list?

Stephen | Data

1,702 subscribers

30,112 Aufrufe • vor 13 Tagen •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

8 Kommentare

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Prachi Rajawatvor 13 Tagen

Thanks for sharingg.

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Bumble bee 🐝vor 13 Tagen

Stephen what solid SQL Project do you recommend doing?

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Nnabuife Max Okonduvor 12 Tagen

Business Analyst

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ᗩᗩvor 12 Tagen

🤝

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Idris Yusuff || Data Analysis Journeyvor 12 Tagen

Thanks sir

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Kaizenvor 12 Tagen

Alex the Analyst

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dummy tunnssvor 12 Tagen

Can we use Linux as a Data analyst sir?

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Edchinvor 12 Tagen

Thank you

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Dear Friend, I wrote this book for you. For the past year, I have labored to create a product that will help you learn and master SQL. I have been there. I have felt the frustration of trying to learn SQL and not knowing where to begin. I have lived through the struggle of setting up a platform to run SQL queries. Most platforms require sign-ups and logins that create a headache for learners. I also know the challenge of finding proper SQL exercises that mirror the real-world experience of a data analyst. Yes, I have been in your shoes. That’s why I created SQL Essentials for Data Analysis: A 50-Day Hands-on Challenge Book (Go From Beginner to Pro). Yes, to give you a clear, practical path from beginner to confident SQL user. ✅Why SQL Still Matters You may be wondering if SQL still matters in 2025. The answer: it has never mattered more. SQL is the lingua franca of data. Data still lives in databases, and the only language it truly understands is SQL. 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You’re learning how SQL is used in real-world scenarios, not just memorizing syntax. By the end of each day, you’ve solved a problem that feels meaningful and practical: yes, something that mirrors data analysts’ and engineers’ work in real life. In this book I use SQLite. I chose SQLite because it’s simple, lightweight, and runs on any system without complicated setups or cloud accounts. You don’t need to worry about complex configurations. SQLite allows you to focus entirely on learning SQL concepts, queries, and logic without distractions. You will just have to import it. I also structured the book for use in Jupyter or Google Colab notebooks. These are playgrounds for data analysts, engineers, and scientists. These environments are interactive and flexible. They let you run queries, visualize results, and experiment in real time. Using notebooks ensures that you can practice SQL while documenting your work and learning at your own pace, all in one place. 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Gary Vaynerchuk

24,023 Aufrufe • vor 2 Jahren

Today's interview is among the most chilling I've ever recorded: Tom Davidson on how AI-enabled coups could allow a tiny group to seize power His new paper, published today, lays out how AGI will naturally destabilise even mature democracies and encourage power grabs. The paper, plus links and transcript, below: 00:50 How AI enables tiny groups to seize power 12:31 Secret AI loyalties 24:32 Are human power grabs more plausible than 'rogue AI'? 37:31 Will AGI make it impossible to escape autocracy? 41:34 Threat 1: AI-enabled military coups 1:00:48 Threat 2: Autocratisation 1:13:31 Threat 3: Self-built hard power 1:21:23 Can you stage a coup with 10,000 drones? 1:29:22 Are people psychologically willing to do coups? 1:33:31 Will a balance of power between AIs prevent this? 1:49:28 How likely is this in the US? 1:56:58 Is a small group seizing power really so bad? 2:00:33 Countermeasure 1: Block internal misuse 2:10:27 Countermeasure 2: Cybersecurity 2:12:36 Countermeasure 3: Model spec transparency 2:21:55 Countermeasure 4: Sharing AI access broadly 2:26:45 Is it more dangerous to concentrate or share AGI? 2:32:38 In defence of open sourcing AI models 2:53:18 Preventing AI-enabled military coups in particular 3:03:00 How to help if you work at an AI company 3:07:09 The power ML researchers still have, for now 3:10:29 How to help if you're an elected leader Find it in any app by searching for 80,000 Hours Podcast.

Today's interview is among the most chilling I've ever recorded: Tom Davidson on how AI-enabled coups could allow a tiny group to seize power His new paper, published today, lays out how AGI will naturally destabilise even mature democracies and encourage power grabs. The paper, plus links and transcript, below: 00:50 How AI enables tiny groups to seize power 12:31 Secret AI loyalties 24:32 Are human power grabs more plausible than 'rogue AI'? 37:31 Will AGI make it impossible to escape autocracy? 41:34 Threat 1: AI-enabled military coups 1:00:48 Threat 2: Autocratisation 1:13:31 Threat 3: Self-built hard power 1:21:23 Can you stage a coup with 10,000 drones? 1:29:22 Are people psychologically willing to do coups? 1:33:31 Will a balance of power between AIs prevent this? 1:49:28 How likely is this in the US? 1:56:58 Is a small group seizing power really so bad? 2:00:33 Countermeasure 1: Block internal misuse 2:10:27 Countermeasure 2: Cybersecurity 2:12:36 Countermeasure 3: Model spec transparency 2:21:55 Countermeasure 4: Sharing AI access broadly 2:26:45 Is it more dangerous to concentrate or share AGI? 2:32:38 In defence of open sourcing AI models 2:53:18 Preventing AI-enabled military coups in particular 3:03:00 How to help if you work at an AI company 3:07:09 The power ML researchers still have, for now 3:10:29 How to help if you're an elected leader Find it in any app by searching for 80,000 Hours Podcast.

Rob Wiblin

48,437 Aufrufe • vor 1 Jahr

Here’s how I would learn data engineering in 2025: 1. The basics: - learn SQL — SELECT, FROM, WHERE, GROUP BY, JOIN, HAVING, etc - learn Python — data structures: objects, arrays, tuples, namedtuples — algorithms: recursion, loops 2. Intermediate - learn distributed compute — pick up PySpark or Snowflake or BigQuery - learn data make architecture — pick up iceberg or delta lake - learn job orchestration — pick up Airflow or Mage - learn data quality — pick up Great expectations 3. Advanced - learn the data modeling techniques — one big table vs kimball vs Inmon vs data vault techniques - learn machine learning features and vector databases — pick up pinecone and how to fine tune LLMs with high quality data My newsletter has a deeper roadmap here:

Here’s how I would learn data engineering in 2025: 1. The basics: - learn SQL — SELECT, FROM, WHERE, GROUP BY, JOIN, HAVING, etc - learn Python — data structures: objects, arrays, tuples, namedtuples — algorithms: recursion, loops 2. Intermediate - learn distributed compute — pick up PySpark or Snowflake or BigQuery - learn data make architecture — pick up iceberg or delta lake - learn job orchestration — pick up Airflow or Mage - learn data quality — pick up Great expectations 3. Advanced - learn the data modeling techniques — one big table vs kimball vs Inmon vs data vault techniques - learn machine learning features and vector databases — pick up pinecone and how to fine tune LLMs with high quality data My newsletter has a deeper roadmap here:

Zach Wilson

29,811 Aufrufe • vor 1 Jahr

Here's my conversation with Pieter Levels (@levelsio), self-taught developer and entrepreneur who designed, programmed, shipped, and ran over 40 startups, many of which are hugely successful. In most cases, he did it all by himself, while living the digital nomad life in over 40 countries and over 150 cities. This was a fun and inspiring conversation! It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:03 - Startup philosophy 9:34 - Low points 13:03 - 12 startups in 12 months 19:55 - Traveling and depression 32:34 - Indie hacking 36:37 - Photo AI 1:12:53 - How to learn AI 1:21:30 - Robots 1:29:47 - Hoodmaps 1:53:52 - Learning new programming languages 2:03:24 - Monetize your website 2:09:59 - Fighting SPAM 2:13:33 - Automation 2:24:58 - When to sell startup 2:27:52 - Coding solo 2:33:54 - Ship fast 2:42:38 - Best IDE for programming 2:52:09 - Andrej Karpathy 3:01:34 - Productivity 3:15:21 - Minimalism 3:24:07 - Emails 3:31:20 - Coffee 3:39:05 - E/acc 3:41:21 - Advice for young people

Here's my conversation with Pieter Levels (@levelsio), self-taught developer and entrepreneur who designed, programmed, shipped, and ran over 40 startups, many of which are hugely successful. In most cases, he did it all by himself, while living the digital nomad life in over 40 countries and over 150 cities. This was a fun and inspiring conversation! It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:03 - Startup philosophy 9:34 - Low points 13:03 - 12 startups in 12 months 19:55 - Traveling and depression 32:34 - Indie hacking 36:37 - Photo AI 1:12:53 - How to learn AI 1:21:30 - Robots 1:29:47 - Hoodmaps 1:53:52 - Learning new programming languages 2:03:24 - Monetize your website 2:09:59 - Fighting SPAM 2:13:33 - Automation 2:24:58 - When to sell startup 2:27:52 - Coding solo 2:33:54 - Ship fast 2:42:38 - Best IDE for programming 2:52:09 - Andrej Karpathy 3:01:34 - Productivity 3:15:21 - Minimalism 3:24:07 - Emails 3:31:20 - Coffee 3:39:05 - E/acc 3:41:21 - Advice for young people

Lex Fridman

2,442,197 Aufrufe • vor 2 Jahren

If you make Power BI reports, I think you might enjoy stepping outside of Power BI to experiment with coding agents and dataviz libraries like Vega, Altair, or d3.js. Here's an example of a dashboard I made with FitBit data. While making the pbir-cli (testing starts this week, thanks to everyone who showed interest!), we learned a lot. Chiefly: we've found it's really, really hard to get an agent to work well with Power BI reports!! Power BI reports are built around abstraction and different intersecting layers. Themes, metadata, extensions, the model... all of it built for a low-code SSBI experience (clicky-clicky-draggy-droppy). That's fine for you and me (mostly). For a coding agent, though, it's inflexible... maybe even hostile. Even with the right tools and context, you simply can't get a Power BI report to reliably do _exactly_ what you want; it's just not meant for that. If you experiment a bit with Vega, Altair, or d3.js... you'll see what I mean; the contrast is pretty clear. This isn't necessarily a bad thing; unlimited flexibility may lead to inconsistency, and there's creativity in constraints. But still, I've been wanting to explore visualization without these constraints... My experiments beyond Power BI reports have been interesting and given me a lot to think about. The most promising approach so far: viz-as-code with custom embedded visuals, pulling from local or remote data sources. This stepcount dashboard is one such example... made in just a few hours between other tasks. Materializing a dashboard like this from natural language wasn't really viable a year ago. Project out another 12–18 months and it's certainly difficult to imagine what the future looks like... That said, reports and dashboards in an enterprise context aren't just visuals. Governance, distribution, integration, etc... years of individual and organizational investment. All of that makes change have a speed limit; we won't be plugging in custom embedded dashboards, overnight. But if you're curious, I do think it's a good investment to step outside Power BI and experiment. Investments you may even be turned into custom visual designs, anyway :). As Havens Consulting put it recently to me: it's time to multiclass...

If you make Power BI reports, I think you might enjoy stepping outside of Power BI to experiment with coding agents and dataviz libraries like Vega, Altair, or d3.js. Here's an example of a dashboard I made with FitBit data. While making the pbir-cli (testing starts this week, thanks to everyone who showed interest!), we learned a lot. Chiefly: we've found it's really, really hard to get an agent to work well with Power BI reports!! Power BI reports are built around abstraction and different intersecting layers. Themes, metadata, extensions, the model... all of it built for a low-code SSBI experience (clicky-clicky-draggy-droppy). That's fine for you and me (mostly). For a coding agent, though, it's inflexible... maybe even hostile. Even with the right tools and context, you simply can't get a Power BI report to reliably do _exactly_ what you want; it's just not meant for that. If you experiment a bit with Vega, Altair, or d3.js... you'll see what I mean; the contrast is pretty clear. This isn't necessarily a bad thing; unlimited flexibility may lead to inconsistency, and there's creativity in constraints. But still, I've been wanting to explore visualization without these constraints... My experiments beyond Power BI reports have been interesting and given me a lot to think about. The most promising approach so far: viz-as-code with custom embedded visuals, pulling from local or remote data sources. This stepcount dashboard is one such example... made in just a few hours between other tasks. Materializing a dashboard like this from natural language wasn't really viable a year ago. Project out another 12–18 months and it's certainly difficult to imagine what the future looks like... That said, reports and dashboards in an enterprise context aren't just visuals. Governance, distribution, integration, etc... years of individual and organizational investment. All of that makes change have a speed limit; we won't be plugging in custom embedded dashboards, overnight. But if you're curious, I do think it's a good investment to step outside Power BI and experiment. Investments you may even be turned into custom visual designs, anyway :). As Havens Consulting put it recently to me: it's time to multiclass...

Kurt Buhler

28,562 Aufrufe • vor 6 Monaten