Month 1: Absolute Basics of Python (Weeks 1-5)

• Week 1: Getting Started with Python (10 hours)
  • Learn: What is Python? Installing (step-by-step: download from python.org; use Anaconda if easier for AI libs later). Hello World print statement. Using online tools like Replit if install fails.
  • AI Tie-in: Python as the “language” for telling AI what to do.
  • Mini-Project: Print “Hello, AI World!” and tweak it.
  • Video Topic: “Python from Zero: My First Setup as a Total Beginner.”
• Week 2: Variables and Data Types (10 hours)
  • Learn: What are variables? Basic types (numbers, text). Simple math operations.
  • AI Tie-in: Storing AI data like numbers for predictions.
  • Mini-Project: Assign and print a number (e.g., your age) and add 1.
  • Video Topic: “Storing Stuff in Python: Variables for AI Beginners.”
• Week 3: Basic Logic and Decisions (10 hours)
  • Learn: If statements (e.g., if number > 10, print “Big!”). Simple conditions.
  • AI Tie-in: Decisions in AI, like classifying if something is “positive” or “negative.”
  • Mini-Project: Check if a number is even/odd.
  • Video Topic: “Making Choices in Code: If-Else for Novices.”
• Week 4: Loops for Repetition (10 hours)
  • Learn: For loops (repeat 5 times). While loops basics.
  • AI Tie-in: Repeating tasks over data, like checking multiple AI inputs.
  • Mini-Project: Print numbers 1-10 in a loop.
  • Video Topic: “Looping Basics: Repeating Code for AI Data.”
• Week 5: Review and Simple Combinations (10 hours)
  • Learn: Mix variables, ifs, loops.
  • AI Tie-in: Basic data checks.
  • Mini-Project: Loop to print even numbers up to 20.
  • Video Topic: “Week 5 Recap: Putting Basics Together as a Newbie.”

Month 1 Milestone: Comfortable running simple scripts. Share a “My First Month Wins” video.

Month 2: Handling Data Structures (Weeks 6-9)

Focus: Storing more data simply. Slower intro to lists/dicts.

• Week 6: Lists – Your First Data Collection (10 hours)
  • Learn: Creating lists, adding/removing items, accessing by position.
  • AI Tie-in: Lists as mini-datasets for AI.
  • Mini-Project: List of fruits; print the first one.
  • Video Topic: “Lists in Python: Grouping Data for AI.”
• Week 7: More on Lists and Loops (10 hours)
  • Learn: Looping over lists, list comprehensions (simple version).
  • AI Tie-in: Processing AI data one by one.
  • Mini-Project: Loop to double numbers in a list.
  • Video Topic: “Working with Lists: Beginner Loops for AI.”
• Week 8: Dictionaries – Key-Value Pairs (10 hours)
  • Learn: Creating dicts, adding keys, accessing values.
  • AI Tie-in: Storing AI settings (e.g., {“model”: “simple”}).
  • Mini-Project: Dict for person info; print age.
  • Video Topic: “Dictionaries: Organizing AI Info Easily.”
• Week 9: Functions – Reusable Code Blocks (10 hours)
  • Learn: Defining simple functions, calling them.
  • AI Tie-in: Reuse code for AI tasks.
  • Mini-Project: Function to add two numbers.
  • Video Topic: “My First Functions: Reusing Code as a Novice.”

Month 2 Milestone: Basic data handler script. “Month 2: Data Basics Mastered” video.

Month 3: Practical Tools and Files (Weeks 10-13)

Focus: Errors, files – with lots of troubleshooting tips.

• Week 10: Handling Errors Gently (10 hours)
  • Learn: Common errors, try-except basics.
  • AI Tie-in: Making AI code not crash on bad data.
  • Mini-Project: Safe addition function.
  • Video Topic: “Fixing Mistakes: Error Handling for Beginners.”
• Week 11: Working with Files (10 hours)
  • Learn: Reading/writing simple text files.
  • AI Tie-in: Loading AI data from files.
  • Mini-Project: Write “Hello” to a file, read it back.
  • Video Topic: “Files in Python: Storing AI Data.”
• Week 12: Modules and Imports (10 hours)
  • Learn: Using built-in modules (e.g., math for sqrt).
  • AI Tie-in: Bringing in tools for AI math.
  • Mini-Project: Import math, calculate square root.
  • Video Topic: “Borrowing Code: Modules for AI Novices.”
• Week 13: Mini-Project Integration (10 hours)
  • Learn: Combine functions, files, lists.
  • AI Tie-in: Simple AI-like data flow.
  • Mini-Project: Read list from file, process with function.
  • Video Topic: “Building a Tiny AI Pipeline.”

Month 3 Milestone: Error-free basic script. “Halfway There” video with Q&A.

Month 4: AI Data Libraries (Weeks 14-17)

Focus: Intro to NumPy/Pandas with visuals.

• Week 14: NumPy – Numbers Made Easy (10 hours)
  • Learn: Arrays, basic operations.
  • AI Tie-in: Fast math for AI.
  • Mini-Project: Create array, add 1 to each.
  • Video Topic: “NumPy Intro: AI Numbers for Beginners.”
• Week 15: More NumPy (10 hours)
  • Learn: Shaping arrays, simple stats.
  • AI Tie-in: Data prep for models.
  • Mini-Project: Average of array.
  • Video Topic: “NumPy Fun: Shaping AI Data.”
• Week 16: Pandas – Tables for Data (10 hours)
  • Learn: DataFrames, reading CSV.
  • AI Tie-in: Handling real AI datasets.
  • Mini-Project: Load small CSV, print head.
  • Video Topic: “Pandas Basics: AI Tables.”
• Week 17: Cleaning Data with Pandas (10 hours)
  • Learn: Drop missing values, simple filters.
  • AI Tie-in: Clean data for better AI.
  • Mini-Project: Clean a sample dataset.
  • Video Topic: “Pandas Cleaning: Novice AI Prep.”

Month 4 Milestone: Data loading/cleaning script. “Data Tools Unlocked” video.

Month 5: Visualization and Stats (Weeks 18-21)

Focus: Seeing data; keep simple.

• Week 18: Matplotlib – Basic Plots (10 hours)
  • Learn: Line plots, labels.
  • AI Tie-in: See AI results.
  • Mini-Project: Plot numbers 1-10.
  • Video Topic: “Plotting with Matplotlib: Visual AI.”
• Week 19: Seaborn – Prettier Plots (10 hours)
  • Learn: Simple bar charts.
  • AI Tie-in: Data insights.
  • Mini-Project: Bar chart from list.
  • Video Topic: “Seaborn for Beginners: AI Views.”
• Week 20: Basic Stats (10 hours)
  • Learn: Mean, median with NumPy/Pandas.
  • AI Tie-in: Analyze AI data.
  • Mini-Project: Stats on sample data.
  • Video Topic: “Simple Stats for AI.”
• Week 21: EDA Integration (10 hours)
  • Learn: Combine data + viz.
  • AI Tie-in: Explore before modeling.
  • Mini-Project: Basic EDA on CSV.
  • Video Topic: “Exploring Data: Novice Style.”

Month 5 Milestone: Visual data report. “Seeing AI Data” video.

Month 6: Intro to ML and DL (Weeks 22-26)

Focus: Simple models; use pre-made datasets.

• Week 22: Scikit-learn Regression (10 hours)
  • Learn: Basic linear model.
  • AI Tie-in: Predictions.
  • Mini-Project: Predict from toy data.
  • Video Topic: “First AI Model: Regression.”
• Week 23: Classification Basics (10 hours)
  • Learn: Simple classifier.
  • AI Tie-in: Categories.
  • Mini-Project: Iris intro.
  • Video Topic: “Classifying with AI.”
• Week 24: Unsupervised and Tuning (10 hours)
  • Learn: Basic clustering, simple tweaks.
  • AI Tie-in: Patterns.
  • Mini-Project: Cluster points.
  • Video Topic: “AI Without Labels.”
• Week 25: TensorFlow Basics (10 hours)
  • Learn: Simple neural net.
  • AI Tie-in: Deep AI.
  • Mini-Project: Basic prediction.
  • Video Topic: “Deep Learning Start.”
• Week 26: Capstone Project (10 hours)
  • Learn: Full simple AI flow.
  • AI Tie-in: End-to-end.
  • Mini-Project: Sentiment or image basics.
  • Video Topic: “6 Months Done: My Novice AI Journey.”

Month 6 Milestone: Complete AI project. Final celebration video.