- 2 days ago
Wizards, join Anastasia, Isabella, Ethan, Sophia, and Olivia for Day 35 of the DailyAIWizard Python for AI series! 🚀 Learn how to use dictionaries to organize AI metadata like {'model': 'WizardNet'} and sets to filter unique data for AI projects. Sophia leads two demos with NumPy, Ethan explains every line, and Olivia adds tips. Perfect for beginners building on Day 34! 💻 Get ready for Day 36: Control Flow in Python. Subscribe, like, and share your ai_metadata.py output in the comments! Join our Discord, X, or Instagram (@DailyAIWizard) for more tips! Code the Future, Wizards!
🔗 Links:
Python: python.org
VS Code: code.visualstudio.com
Website: dailyaiwizard.com
Discord: discord.com/channels/1397945816349675600/1397945819260391521
X: x.com/dailyaiwizard
Instagram: www.instagram.com/dailyaiwizard
Hashtags:
#Python #LearnPython #PythonForAI #AICoding #PythonTutorial #CodingForBeginners #PythonDictionaries #PythonSets #AIProgramming #TechTutorial #DailyAIWizard #CodeTheFuture
Tags:
Python, Learn Python, Python for AI, AI Coding, Python Tutorial, Coding for Beginners, Python Dictionaries, Python Sets, AI Programming, Tech Tutorial, Python 3, Coding Journey, VS Code, Beginner Programming, Data Science, DailyAIWizard, Code the Future
🔗 Links:
Python: python.org
VS Code: code.visualstudio.com
Website: dailyaiwizard.com
Discord: discord.com/channels/1397945816349675600/1397945819260391521
X: x.com/dailyaiwizard
Instagram: www.instagram.com/dailyaiwizard
Hashtags:
#Python #LearnPython #PythonForAI #AICoding #PythonTutorial #CodingForBeginners #PythonDictionaries #PythonSets #AIProgramming #TechTutorial #DailyAIWizard #CodeTheFuture
Tags:
Python, Learn Python, Python for AI, AI Coding, Python Tutorial, Coding for Beginners, Python Dictionaries, Python Sets, AI Programming, Tech Tutorial, Python 3, Coding Journey, VS Code, Beginner Programming, Data Science, DailyAIWizard, Code the Future
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LearningTranscript
00:00Hello, Wizards. I'm Anastasia, your guide for Day 35 of the daily AI Wizard Python for AI series, and I'm thrilled to dive into dictionaries and sets.
00:09After conquering lists and tuples in Day 34, today we'll explore these powerful tools for organizing AI data, like model metadata or unique features.
00:19Get ready for an epic journey with demos and challenges that'll ignite your coding passion. Let's code the future, Wizards.
00:25Hey, Wizards. I'm Isabella, and I'm so excited you're here to unlock the magic of dictionaries and sets.
00:33These structures are like enchanted vaults for storing key-value pairs or unique data, perfect for AI tasks like tracking model parameters.
00:42Join us for vibrant demos and a challenge that'll make your Python skills shine.
00:47Ethan here, Wizards. I'll break down the code for dictionaries and sets' bio data.
00:52Sets are like magical filters that keep only unique data, and dictionaries organize data efficiently.
00:58Both are AI essentials.
01:00Stick with us to master these tools and level up your coding game.
01:04Sophia here, Wizards.
01:07I'm pumped to lead today's demos, showing you dictionaries and sets in action for AI.
01:12Get ready for some serious coding magic.
01:15Olivia here. I'll share tips and ask questions to make your learning smooth and fun.
01:23Let's dive into dictionaries and sets, Wizards.
01:27Wizards, dictionaries, and sets are game changers for AI coding.
01:31Dictionaries store key-value pairs, like a model's name and accuracy,
01:36making data retrieval lightning-fast for AI applications.
01:39Sets keep only unique items, perfect for filtering duplicate features and data sets.
01:45These tools streamline your AI projects, and we'll show you how in our demos.
01:50Absolutely, Anastasia.
01:52Imagine organizing model metadata in a dictionary, or ensuring unique data points in a set.
01:58These are real-world AI superpowers.
02:01Today's lesson builds on Day 34 and preps you for Day 36's control flow.
02:06Get ready to organize data like a true wizard.
02:10Wizards, today we're unlocking dictionaries and sets, your keys to mastering AI data.
02:16You'll learn to create dictionaries for structured data,
02:19manage unique items with sets, and apply them in AI with NumPy demos.
02:24Our challenge will spark your creativity, so let's dive into this magical coding journey.
02:30Sophia's leading our demos with energy,
02:32Ethan's explaining every line,
02:33and Olivia's got your back with tips.
02:36By the end, you'll handle AI data like a wizard, ready for Day 36 control flow.
02:42This is your chance to shine in Python.
02:45Wizards, meet your Day 35 dream team.
02:50Anastasia and I are here to guide you with clear, engaging explanations,
02:54making dictionaries and sets fun to learn.
02:57Ethan's our code expert, diving deep into every line to ensure you grasp the magic.
03:01Sophia's leading our demos with infectious enthusiasm,
03:06showing you how to wield dictionaries and sets for AI.
03:09Olivia's here with setup tips and questions to keep you on track.
03:13We're all dedicated to making you an AI coding wizard.
03:16Let's get started.
03:17Wizards' dictionaries are like enchanted vaults that store data as key value pairs,
03:23like model info, wa, la, name, AI wizard model, accuracy, 0.85.
03:31They're perfect for organizing AI metadata, letting you access values instantly with keys.
03:37You'll see how dictionaries streamline AI projects in our demos.
03:42Anastasia, how do we create a dictionary and why is it so useful for AI?
03:47A great question, Olivia.
03:49Use curly braces like ski value to create one,
03:52and it's useful because it organizes complex AI data,
03:56like model parameters for quick access.
03:58We'll show you how to build and use dictionaries in our demos wizards.
04:01Sets are like magical filters that store only unique items, wizards-like features.
04:090.5, 1.2, 2.8.
04:12They're perfect for AI tasks,
04:15like ensuring no duplicate data points in a dataset.
04:18Sets are fast and efficient and will show their power in our demos.
04:22Exactly, Anastasia.
04:24Sets automatically remove duplicates,
04:27making them ideal for cleaning AI feature data before analysis.
04:30You'll learn to create sets with curly braces and use them with NumPy for AI.
04:36Get ready to filter data like a wizard.
04:39Wizards, dictionaries, and sets serve unique AI purposes.
04:43Dictionaries organize structured data, like model metadata,
04:47with fast key-based access, perfect for AI configurations.
04:52Sets ensure uniqueness, like filtering duplicate features,
04:55which is critical for clean AI datasets.
04:58Think of dictionaries as your AI organizer,
05:01storing key-value pairs for quick lookups, like model accuracy.
05:06Sets are your data purifiers,
05:08ensuring no redundant data in AI tasks.
05:11Our demos will show you how to use both to power your AI projects.
05:15Wizards, creating a dictionary is simple.
05:19Use curly braces like model on info,
05:22Chizakalak name,
05:24AI wizard model,
05:26accuracy 0.85.
05:28You can store strings, numbers, or even lists as values,
05:32making dictionaries versatile for AI metadata.
05:35Try it in the Python shell or a .pi file,
05:38and we'll show you how in our demos.
05:40Olivia's right.
05:43Dictionaries are perfect for organizing complex AI data,
05:47like model parameters,
05:48because keys make retrieval fast.
05:51Use descriptive keys like accuracy to keep your code clear.
05:54Let's build dictionaries to power your AI projects, wizards.
05:58Wizards.
05:59Sets are created with curly braces,
06:02like features,
06:04Thash to trees,
06:05Thao 0.5,
06:061.2,
06:072.8,
06:09and automatically remove duplicates.
06:12They're ideal for AI tasks,
06:14like ensuring unique feature values in a dataset.
06:17Sets are fast and unordered,
06:19and we'll show their magic in our demos.
06:22Sets are super efficient for AI, wizards.
06:24If you add 0.5 twice to features,
06:27it only appears once.
06:29You can perform operations like unions to combine sets,
06:33which we'll demonstrate for AI data cleaning.
06:35Wizards.
06:36Access dictionary values using keys,
06:39like model underscore info,
06:41name,
06:41to get AI wizard model.
06:44Keys act like labels,
06:45making data retrieval instant for AI tasks,
06:48such as fetching model accuracy.
06:50If a key doesn't exist,
06:52you'll get a key error,
06:53so we'll show you how to handle it.
06:55Ethan,
06:56what happens if I use a wrong key?
06:57How do I avoid errors?
07:00Great question, Olivia.
07:01Use model underscore info dot get key default
07:05to avoid key errors by returning a default value
07:08if the key's missing.
07:10This is super useful for AI data,
07:12and we'll demo it.
07:13Wizards.
07:15Wizards.
07:15Sets shine with operations like union,
07:18intersection,
07:20and difference.
07:21For example,
07:22features dot union new features
07:25combines two sets,
07:27keeping only unique items,
07:29perfect for merging AI data sets.
07:32These operations are fast
07:33and make data cleaning a breeze.
07:35In our demo,
07:37we'll use union
07:38to combine feature sets
07:40for AI analysis.
07:42Sets also support add
07:43to insert items
07:44and remove
07:45to delete them.
07:47These tools are key
07:48for ensuring clean,
07:49unique data in AI projects.
07:51Wizards.
07:52Wizards dictionaries are mutable
07:54so you can update them.
07:56Add a new key value pair
07:57with model info accuracy,
07:59chart 0.85,
08:01or change an existing one
08:03like model info epochs,
08:05chagov 200.
08:07This flexibility is perfect
08:09for updating AI model metadata
08:12in real time.
08:14You can also use update
08:15to add multiple pairs at once,
08:17like model underscore info.
08:20Update.
08:20Layers.
08:21Three.
08:22Neurons.
08:2264.
08:24Deleting keys with pop
08:25or del keeps your dictionary
08:27lean.
08:28We'll show these updates
08:29in our demo,
08:30Wizards.
08:31Wizards.
08:32Sets don't maintain order,
08:33which makes them unique.
08:35They focus on ensuring
08:36items are distinct,
08:38like 0.5,
08:391.2,
08:402.8,
08:42perfect for AI tasks
08:43where duplicates
08:44could skew results.
08:46Their speed and simplicity
08:47make sets a go-to
08:48for data cleaning.
08:50Anastasia,
08:51why don't sets keep order
08:52like lists?
08:54Great question, Olivia.
08:56Sets prioritize
08:56uniqueness and speed
08:58over order,
08:59which is ideal for tasks
09:00like filtering AI features.
09:02You'll see how sets shine
09:03in our demo, Wizards.
09:05Wizards.
09:06Dictionaries offer methods
09:08like keys,
09:09values,
09:10and items
09:10to access data.
09:12For example,
09:13model underscore info.
09:15Keys.
09:16Returns all keys,
09:17like name,
09:18accuracy.
09:20These methods are essential
09:21for navigating AI metadata
09:22efficiently in your projects.
09:24Methods make dictionaries
09:26versatile for AI wizards.
09:29Use items
09:29to loop through
09:30key value pairs
09:32or popitum
09:32to remove the last pair.
09:35We'll demo keys
09:36to show you
09:37how to extract data
09:38like a pro.
09:39Navigate AI data easily.
09:42Wizards,
09:43it's demo time
09:44and I'm so excited
09:45to lead you through
09:46two AI-focused scripts.
09:48We'll use dictionaries
09:49to manage model metadata
09:50and sets to filter
09:51unique features,
09:53both powered by
09:53number py for real AI magic.
09:56Get your Python setup ready
09:58and let's make
09:59data organization fun.
10:02Sophia's demos
10:03will show you dictionaries
10:04and sets in Action Wizards,
10:06ensure Python,
10:07VS Code,
10:08and NumPy
10:09are installed
10:09from day 32
10:10and create dictionaries.py
10:13and sets.pi.
10:14Ethan and Olivia
10:16will guide you
10:17with code explanations
10:18and tips.
10:19Let's code.
10:20Wizards,
10:21let's prep for our demos
10:22to make them seamless.
10:25Open VS Code,
10:26create dictionaries.py
10:27and sets.py
10:29and save them
10:29in a Python demo folder.
10:32Run pip install NumPy
10:33to ensure NumPy's ready
10:34and I'll show you
10:35how to run these scripts
10:36like a pro.
10:39Sophia,
10:40what if wizards
10:41forgot how to set up
10:42NumPy
10:42or their environment?
10:43Awesome question, Olivia.
10:47Run pip install NumPy
10:48in a terminal
10:49and activate
10:50your virtual environment
10:51with source my
10:52and slash bin
10:53slash activate
10:54if used.
10:55This ensures
10:56our AI demos
10:57run smoothly,
10:58wizards.
10:59Get your demo ready.
11:02Wizards,
11:03our first demo
11:04in dictionaries.py
11:05creates a dictionary
11:06to store AI model metadata
11:08like name and accuracy.
11:10We'll add a new key,
11:12access values,
11:13and list keys
11:13to show how dictionaries
11:15organize data.
11:16This is your chance
11:17to see AI data management
11:19in action.
11:20Let's do it.
11:22The code is
11:23model underscore info
11:25equals
11:26name
11:26AI wizard model
11:28learning underscore rate
11:290.01
11:31epics
11:32100.
11:34We add model underscore info
11:36accuracy
11:36equals 0.85
11:38and print keys
11:39with list
11:40model underscore info
11:41keys.
11:43This shows how dictionaries
11:45streamline AI metadata
11:46wizards.
11:47Wizards,
11:48model underscore info
11:50equals
11:50name
11:51AI wizard model
11:52learning underscore rate
11:540.01
11:55creates a dictionary
11:57with key value pairs
11:58for AI metadata.
12:00Each key,
12:01like name,
12:02maps to a value,
12:03like AI wizard model,
12:04for instant access.
12:06This structure is perfect
12:08for organizing complex
12:09AI data efficiently.
12:11I love how dictionaries
12:12make AI data
12:13so accessible,
12:14Ethan.
12:16Wizards,
12:16you can store
12:17any data type
12:18as values,
12:19like numbers
12:19or strings,
12:20and retrieve them
12:21with keys.
12:22Try adding your own
12:24key value pair
12:25to see the magic.
12:27In print,
12:28model underscore info
12:30name,
12:31we retrieve
12:32AI wizard model
12:33using the
12:33name
12:34key,
12:35perfect for AI tasks
12:36like fetching model details.
12:39Model underscore info
12:40accuracy
12:41equals
12:420.85
12:43adds a new
12:44key value pair
12:45and list
12:45model underscore info
12:47keys
12:48lists all keys.
12:50These operations
12:51make dictionaries
12:52a powerhouse
12:53for AI data management.
12:55That's so cool,
12:56Ethan.
12:57Wizards,
12:58printing dictionary values
12:59helps you check
13:00your AI data
13:01and updating keys
13:02lets you adapt
13:03as projects evolve.
13:05Try printing your own
13:06dictionary to see it
13:07in action,
13:08it's like opening
13:09a treasure vault.
13:11Wizards,
13:12let's run
13:13dictionaries.py
13:14In VS Code,
13:16open the terminal
13:17with control plus
13:18or cmd plus,
13:19type python3
13:20dictionaries.py
13:21and hit enter.
13:23You'll see your
13:24model metadata
13:25like name and accuracy,
13:27proving your AI data
13:28skills are top notch.
13:30The output shows
13:32model info,
13:33name,
13:34AI wizard model,
13:37model name,
13:38AI wizard model,
13:40and more.
13:42It's like casting a spell
13:44to reveal your AI data.
13:46Try it and share
13:47your results, wizards.
13:49Wizards,
13:50our second demo
13:51in sets.py uses sets
13:53to filter unique AI features
13:54and combine them
13:55with number py.
13:57We'll create a set,
13:58merge it with another,
13:59and convert it
14:00to a number py array
14:01for AI analysis.
14:03This is your chance
14:04to master clean data
14:06for AI projects.
14:08The code creates
14:09features equals
14:100.5,
14:121.2,
14:130.5,
14:142.8,
14:15which removes duplicates,
14:17and unique underscore
14:18features equals features.
14:20Union,
14:21new underscore features,
14:22combines sets.
14:23We convert to a numpy array
14:25with np.
14:27Array,
14:27list,
14:28unique underscore features,
14:30for AI math.
14:31It's pure AI magic,
14:33wizards.
14:34Wizards,
14:35features equals,
14:360.5,
14:371.2,
14:380.5,
14:392.8,
14:40creates a set
14:41that keeps only unique values,
14:43like,
14:430.5,
14:451.2,
14:462.8.
14:47This is perfect for AI
14:49to avoid duplicate data points
14:50in feature sets.
14:52Sets are unordered
14:53but lightning fast
14:54for data cleaning.
14:56I love how sets
14:57simplify AI data,
14:58Ethan.
14:59Wizards,
15:00sets ensure
15:01your feature data
15:01is clean and unique,
15:03ready for analysis.
15:05Try creating your own set
15:07to see the duplicate
15:07removing magic.
15:10In unique underscore features
15:11equals features.
15:13Union,
15:14new underscore features.
15:16We combine two sets
15:17to get all unique items,
15:19like,
15:190.5,
15:201.2,
15:222.8,
15:223.5.
15:24Operations like intersection,
15:26find common items,
15:27and difference,
15:28finds unique ones.
15:30These are key for merging
15:31or filtering AI datasets.
15:33That's so powerful,
15:35Ethan.
15:37Wizards,
15:37set operations let you clean
15:39and combine AI data efficiently,
15:41like merging feature sets.
15:43Try Union,
15:44in our demo,
15:45to see how it streamlines
15:46your AI workflow.
15:49Wizards,
15:50NP underscore array
15:51equals NP.
15:53Array,
15:53list,
15:54unique underscore features,
15:56converts a set to a numpy array
15:57for AI math,
15:58like,
15:590.5,
16:001.2,
16:012.8,
16:023.5.
16:04Arrays are optimized
16:05for operations like matrix calculations
16:07in neural networks.
16:09This step makes your set data AI ready.
16:12I love how sets and number py team up,
16:14Ethan.
16:16Wizards,
16:17converting sets to arrays
16:18powers up your AI models
16:19with clean,
16:20unique data.
16:21Try it in our demo,
16:23to see the transformation.
16:26Wizards,
16:27let's run sets.py.
16:29In VS Code's terminal,
16:31type python3 sets.py
16:33and hit enter.
16:35You'll see unique features,
16:36and a number py array,
16:38showing how sets clean AI data,
16:39like magic.
16:42The output shows unique features,
16:440.5,
16:451.2,
16:462.8,
16:483.5,
16:49numpy array,
16:500.5,
16:511.2,
16:532.8,
16:543.5,
16:55and more.
16:56It's like casting a spell
16:57to purify your AI data.
17:00Share your results, Wizards.
17:02Wizards,
17:03you can loop through dictionaries
17:04using for key in model underscore info.
17:07To access keys or for key,
17:08value in model underscore info.
17:11Items,
17:12for pairs.
17:13This is perfect for processing AI metadata,
17:16like printing all model parameters.
17:18Iteration makes dictionaries dynamic for AI workflows.
17:22Looping is like flipping through your AI spellbook, Wizards.
17:26Use items,
17:27to process key value pairs,
17:29like model names and accuracies,
17:31in a loop.
17:32Try it in the Python shell
17:34to see how it powers your AI projects.
17:38Wizards,
17:38no output from dictionaries py?
17:41Check Python's path with Python 3 version
17:43and ensure dictionaries.py is saved in your current folder.
17:47Use PWD to verify.
17:49Navigate with CD Python demo if needed
17:52and your demo will run smoothly.
17:53For sets.py,
17:56a module not found error,
17:58no module named numpy,
18:00means numpy's missing.
18:02Run pip install numpy.
18:04Verify your code matches ours
18:05and check Python 3.11 or later.
18:09Drop errors in the comments,
18:11Wizards,
18:11we're here to help.
18:13Wizards,
18:14virtual environments are like magical bubbles
18:16for your projects.
18:18Create one with Python 3,
18:19mvenvmynv,
18:21and activate it.
18:23With source,
18:24myenvbin,
18:25activate on Mac Linux,
18:27or myenvju scripts,
18:29activate on Windows.
18:31This isolates numpy for sets pi,
18:34keeping your AI projects clean.
18:37Olivia,
18:38why are virtual environments crucial for AI?
18:41They prevent library conflicts,
18:43Anastasia,
18:44ensuring numpy and other tools
18:46work perfectly for each project.
18:49It's like a dedicated spellbook
18:51for your AI code.
18:53Try it for your demos, Wizards.
18:56Wizards,
18:57open the Python shell with Python 3
18:59and try info,
19:00yashter,
19:01name,
19:02wizard,
19:03score,
19:0495,
19:05print,
19:05info.
19:06Add a key with info level,
19:09and 2,
19:09and print again to see the update.
19:12The shell's a playground
19:12for testing dictionaries instantly.
19:15It's a fantastic way to experiment, Wizards.
19:18Try print info name,
19:19to get wizard or print info dot keys
19:21for all keys.
19:24The shell preps you for day 36 control flow
19:26by letting you test dictionaries hands-on.
19:30Wizards,
19:31dictionaries,
19:31and sets power AI libraries.
19:34Dictionaries store model configurations
19:36in TensorFlow
19:36or metadata in Pandas,
19:39while sets ensure unique data points
19:41in NumPy arrays.
19:42These structures are your foundation
19:44for efficient AI data handling.
19:47You're already using sets with NumPy,
19:50Wizards.
19:50That's a huge step.
19:52In day 36,
19:54control flow will build on this
19:55for smarter AI logic.
19:58Keep practicing dictionaries and sets
19:59to dominate AI coding.
20:02Wizards,
20:03save dictionaries dot pi
20:04and sets dot pi
20:06in VS code with
20:07Cottrell plus S
20:08or CMD plus S.
20:10It's like locking your spells
20:11in a vault.
20:12Store them in a Python demo folder
20:14and back them up
20:15on GitHub or cloud storage.
20:17Your AI code is a treasure
20:18worth protecting.
20:20Share your scripts
20:21on GitHub, Discord,
20:22or here in the Commons,
20:24Wizards.
20:25Your dictionaries and sets
20:26are proof of your AI coding skills.
20:29Show them off.
20:30Saving ensures you're ready
20:32for day 36
20:33control flow adventures.
20:35Wizards,
20:36here's your challenge.
20:37Create AI metadata dot pi
20:39with a dictionary like
20:40model,
20:42wizard net,
20:43accuracy,
20:440.9,
20:45and a set like
20:461.1,
20:472.2,
20:481.1.
20:49Add a key to the dictionary,
20:51merge the set with another,
20:52and print results
20:53with Python 3
20:54AI metadata dot pi.
20:57Share your output
20:57in the comments
20:58or on Instagram.
21:00This is so exciting,
21:01Wizards.
21:02Try adding layers,
21:04three casts a door
21:05into your dictionary
21:06and printdike dot keys.
21:08Show us your results
21:09on YouTube
21:10or Daily AI Wizard.
21:12It's like casting
21:12an AI spell.
21:14Prep for day 36
21:16with this challenge.
21:18Wizards,
21:18hit subscribe,
21:19like this video,
21:21and share your
21:21AI metadata dot pi
21:23output in the comments.
21:25Got questions
21:25about dictionaries or sets?
21:27We're here to help you excel.
21:29Join our Discord
21:30or here to connect
21:31with Wizards
21:32and boost your AI skills.
21:34Our community
21:35is a magical hub,
21:37Wizards.
21:38Post your code,
21:39ask for tips,
21:40or share your wins
21:41on Discord,
21:42here,
21:43or Instagram,
21:44at halfdahlia wizard.
21:46Subscribe for day 36's
21:48control flow,
21:49and let's code
21:50the future together.
21:52Wizards,
21:53day 36 is next,
21:55control flow in Python.
21:56You'll learn to make
21:58decisions and loops
21:59in your code,
22:00like if statements
22:00for AI logic,
22:02building on your dictionary
22:03and set skills.
22:05Get ready for smarter
22:06AI programming.
22:08Control flow will make
22:09your AI code
22:10dynamic, Wizards.
22:11Subscribe to catch day 36,
22:13and keep practicing dictionaries
22:15and sets.
22:16It's another step toward
22:18mastering Python for AI.
22:20Wizards,
22:21you've conquered dictionaries
22:22and sets.
22:23Huge congratulations.
22:25Your dictionaries.pi
22:27and sets.pi demos
22:28prove you're a pro
22:29at organizing AI data.
22:31Keep practicing
22:32and get excited
22:33for day 36's
22:34control flow
22:35to make your code
22:36even smarter.
22:38I'm incredibly proud
22:39of you, Wizards.
22:40You've mastered dictionaries
22:41for structured AI metadata
22:42and sets for clean,
22:44unique data,
22:45skills that power
22:46real-world AI projects
22:47like neural networks
22:48and data pipelines.
22:51Share your
22:51aimetadata.py output
22:53in the comments
22:55or on Instagram,
22:56halfdailyaiwizard,
22:58to show off your magic.
22:59Subscribe,
23:00hit the bell,
23:01and join our Discord.
23:02Or here,
23:03to connect with other Wizards,
23:04ask questions,
23:05and share insights.
23:08Day 36's
23:08control flow
23:09will add logic
23:10to your AI code,
23:11so keep your Python
23:12setup ready.
23:14You're shaping
23:14the future of AI Wizards.
23:16Keep shining,
23:17and let's make more
23:18coding magic together.
23:20You nailed dictionaries
23:21and sets, Wizards.
23:23Your AI data skills
23:24are top tier,
23:25and I loved breaking
23:26down the code for you.
23:27Get ready for day 36's
23:29control flow adventures.
23:31Wizards,
23:32you're absolutely
23:33phenomenal.
23:35Leading these demos
23:36was a blast,
23:37and seeing you
23:37master dictionaries
23:38and sets
23:39is pure AI magic.
23:41Share your
23:42AI underscore
23:42metadata.py results
23:44with it daily
23:45AI wizard on Instagram
23:46or in the comments,
23:47I can't wait
23:48to see your work.
23:49Subscribe for
23:50day 30
23:51SIXS
23:51control flow
23:52lesson,
23:53join our Discord
23:53or X community,
23:55and keep coding
23:55with confidence.
23:57You're true Wizards,
23:58building the AI
23:59future one line
24:00at a time.
24:02Let's code the future,
24:03Wizards.
24:05You crushed dictionaries
24:07and sets, Wizards.
24:09Your AI skills
24:10are soaring,
24:11and I'm thrilled
24:12to be part
24:13of your journey.
24:14Let's dive
24:15into day 36 together.
24:16future.
24:17You
24:18will
24:18first
24:18take a
24:20step
24:31of your
24:32journey.