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42lessons ready on any device
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Course library
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42 lessons · Notes, practice, flashcards, and quizzes work offline
Current lectures from the program’s dual-track work in data architecture and visual communication.
Use Excel’s row-column grid as a bridge to database thinking, then turn raw information into a clear written report and an audience-ready presentation.
1Lesson 1Treat graphic design as intentional communication by using layout, grid systems, alignment, spacing, scale, and focal points to guide the viewer in a deliberate order.
Foundational web, file, research, and programming skills for first-time digital learners.
Preview the learning journey from web navigation and files to programming logic, and establish shared classroom routines for practicing on limited devices.
2Lesson 2Navigate websites efficiently, judge sources by evidence rather than domain alone, cite information, and verify online or AI-generated claims before sharing them.
3Lesson 3Recognize common image, document, video, archive, text, and table formats, then organize files so they remain findable, compatible, and safe to share.
4Lesson 4Use print statements, booleans, variables, operators, loops, and conditionals to understand how a Python program stores information and controls what happens next.
5Lesson 5Store multiple values in indexed lists and organize repeated logic into functions with parameters, return values, and clear names.
Files, APIs, object-oriented programming, and a complete data-backed console capstone.
Review Python’s core types and structures, distinguish representation from meaning, and write readable code with descriptive names, small functions, and predictable behavior.
2Lesson 2Read and write files safely, choose CSV for flat tables and JSON for structured data, and use context managers and libraries to avoid data loss.
3Lesson 3Understand request-response communication, use HTTP methods and status codes, parse JSON, and handle timeouts or errors when Python depends on an external service.
4Lesson 4Model related data and behavior with classes and objects, initialize unique state through constructors, and use encapsulation, inheritance, and polymorphism intentionally.
5Lesson 5Combine OOP, JSON or CSV persistence, reusable functions, dictionaries, console commands, and Matplotlib into a complete item-listing project that can be demonstrated.
EDA, regression, classification, neural networks, and careful model tuning through real examples.
Begin machine learning by understanding the data: distinguish categorical and quantitative variables, visualize distributions and relationships, and look for sample bias before modeling.
2Lesson 2Fit and interpret a linear model, explain slope and intercept in context, inspect residual error, and use held-out test data to estimate performance on new examples.
3Lesson 3Compare linear and polynomial models with mean squared error, add complexity only when it improves unseen predictions, and diagnose underfitting and overfitting.
4Lesson 4Move from predicting numbers to classifying outcomes with logistic regression, probability thresholds, confusion-aware evaluation, and a real public-health example.
5Lesson 5Build intuition for neural networks by tracing features through weighted neurons, layers, activation functions, loss, and the learning process that adjusts weights.
6Lesson 6Follow the full training loop—forward pass, loss, backpropagation, and repeated updates—then tune network capacity and validation performance without chasing training error.
Build a trustworthy professional presence with modern productivity, automation, coding, and AI skills.
Separate personal sharing from professional positioning, use each platform for its strengths, and build relationships through useful, safe, and consistent participation.
2Lesson 2Use Gmail and cloud office tools as one organized system for communication, file storage, collaboration, and professional project delivery.
3Lesson 3Compare visual app automation with desktop scripting, then design a trigger-action workflow that saves time without hiding mistakes or removing necessary review.
4Lesson 4Build trust online with fast, mobile-friendly pages, consistent visual choices, clear navigation, accessible contrast, and content written for the visitor’s task.
5Lesson 5Learn Python’s readable syntax and core data types, then combine input, variables, operators, conditions, and loops into a small useful script.
6Lesson 6Organize real-world information with lists, tuples, and dictionaries, and extend Python with libraries rather than rebuilding common tools from scratch.
7Lesson 7Use generative and agentic AI as assistants—not authorities—by supplying context, protecting sensitive information, checking results, and retaining ownership of decisions.
Career communication, productivity, automation, web fundamentals, Python, and responsible AI.
Build a clear, achievement-focused resume and write professional emails that make a strong first impression for jobs, partnerships, and entrepreneurship.
2Lesson 2Use social platforms intentionally: protect your account, shape a credible professional presence, and build relationships without sharing information that creates risk.
3Lesson 3Organize cloud files, communicate through Gmail, and collaborate safely in Docs, Sheets, Slides, and Drive using the right sharing permission.
4Lesson 4Turn repetitive work into reliable workflows by connecting a trigger to one or more actions, testing the result, and adding conditions only when they are useful.
5Lesson 5Evaluate websites through usability, accessibility, performance, mobile design, and content clarity while learning how HTML, CSS, and JavaScript work together.
6Lesson 6Write a first Python program using values, variables, input, operators, decisions, and loops while learning why readable syntax makes Python beginner-friendly.
7Lesson 7Choose between lists, tuples, and dictionaries to store related information, then use common methods and libraries to solve practical problems.
8Lesson 8Understand how data powers machine learning and generative AI, write more useful prompts, and verify outputs before using them in school, work, or public communication.
A practical path from computer basics to a credible online business presence and safer digital operations.
Start with the digital divide, essential computer parts, safe device handling, and the practical technology skills that support communication, learning, and earning.
2Lesson 2Design for real people by considering their intent, expectations, attention, emotions, and prior experience instead of choosing visuals only because they look attractive.
3Lesson 3Use free social platforms to communicate across distance, share work consistently, build trust, and discover opportunities while keeping a professional identity.
4Lesson 4Learn what AI and large language models do, how transformer-based systems learn patterns, and why useful AI work still requires clear instructions and human checking.
5Lesson 5Create clear visual communication in Canva by starting from purpose, choosing a strong template, and keeping typography, color, imagery, and branding consistent.
6Lesson 6Plan and publish a simple personal website that explains who you are, proves what you can do through projects, and gives visitors a clear way to contact you.
7Lesson 7Recognize creative work protected by copyright, document your own creation process, seek permission before reuse, and understand why business registration differs by country.
8Lesson 8Protect accounts and information by recognizing phishing and social engineering, using layered security, and responding calmly when a message creates urgency or fear.
9Lesson 9Use no-code automation as a force multiplier for small teams by mapping repetitive work, selecting triggers and actions, and protecting the quality of stored data.