Python Dictionaries and Data Modeling: Free Course

About this course

Study Python Dictionaries and Data Modeling in this free English video course from Khan Academy. The classroom preserves all 10 published source recordings, totaling approximately 1h 24m, with their original lesson titles and sequence. The selected curriculum focuses on program structure, reproducible examples and independent problem solving. Use the videos to follow an explanation, examine an example and develop a study output you can check independently. The course title describes this recorded subject or learning track; your study can extend beyond watching through the practical activities below.

Course at a glance

What you’ll learn

• Follow the explanation and worked reasoning in “Datasets and data structures”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Dictionary hashing”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Program design: bakery inventory”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Accessing nested data”, then describe the main idea in your own words.
• Connect examples across Python Dictionaries and Data Modeling by identifying the terms, assumptions and methods they use.
• Create a small independent practice output and check it against the relevant teaching explanation.

Skills you’ll gain

• Python
• Program structure
• Tracing
• Debugging

Course Overview

The source curriculum is presented as a complete recorded video edition of Python Dictionaries and Data Modeling. Representative lessons include “Datasets and data structures”, “Program design: bakery inventory” and “Dictionaries full-unit review”. These recordings give concrete examples to revisit while building program structure, reproducible examples and independent problem solving. Their place in the lesson list is preserved, so you can return to a particular explanation without losing its source position. Introductions, demonstrations, examples, reviews and compilations remain included whenever they appear in the original playlist. Reading a lesson title is useful for locating a topic; working through its reasoning and checking a practice attempt is what makes the recording valuable for learning.

How to study the course

• Videos 1–2: this part of the source list includes “Datasets and data structures” through “Dictionaries”. State the intended input, operation and result. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
• Videos 3–5: this part of the source list includes “Dictionary hashing” through “Program design: bakery inventory”. Reproduce a demonstration before modifying it. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
• Videos 6–7: this part of the source list includes “Data modeling and APIs” through “Accessing nested data”. Trace behavior and investigate unexpected output. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
• Videos 8–10: this part of the source list includes “Program design: emergency response” through “Dictionaries full-unit review”. Check the example with a changed condition. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.

Who is this for?

This course suits learners studying the specific programming or computing topic. It also provides a recorded reference for revisiting a topic after an earlier lesson or study attempt. Choose examples appropriate to your background and allow time to work through the method instead of judging understanding only by how familiar the terminology sounds.

Before you start

Use a suitable practice environment for the language or tool shown in the recordings. Earlier programming knowledge is useful for topic courses that build on variables, functions or data structures. Prior familiarity with Python variables and control flow will make the examples easier to follow.

Put the lessons into practice

Build a small example using two techniques demonstrated in the recordings. State the intended result, run or trace the example and explain how its parts work together. Try a normal case and a changed input or condition. Record the difference between the expected and actual results, then correct one problem using the course’s debugging or reasoning approach. Keep the final example small enough that you can explain every important step. Finish with a short note on one improvement and the evidence that it worked.

This optional study activity is provided by WikiFree for independent practice. Keep your working notes and use the relevant classroom recording to check a step, definition or interpretation. It is not an instructor-marked assignment.

Certificate / Assessment

Watching the public videos and using WikiFree completion tracking does not award a certificate, academic credit, an examination voucher or instructor assessment. Use your practice output to review what you can explain and repeat independently. The recorded lessons provide study material; completion tracking records your progress through that material.

Frequently asked questions

Provider: Khan Academy. Videos play from the Khan Academy channel on YouTube.