Free through lesson 3

Careers & Portfolios for Beginners

Choosing a project, estimating its size, finishing it, writing a README and publishing, the work history document (shokumu keirekisho), coding tests, interviews, and your first three months on the job. Over 20 lessons, you'll get to the point where you can "write down only what you can verify from the repository on your own machine." We skip generalizations we can't back up, and include only command output, git history, and practice problems we actually solved.

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Curriculum

The 20 lessons are split into 5 chapters. We recommend going in order from chapter 1, but feel free to skim just the parts you're curious about. Note: This course deals with topics that have no single right answer. We don't write generalizations we can't back up, and we don't include numbers we can't cite a source for (salaries, pass rates, average number of applications). Code in the hands-on lessons runs right in your browser. The thinking behind it is also covered in Your First Portfolio and The Real Reason You Can't Stick With Learning to Program.

Chapter 1 — Deciding What to Build (lessons 1–5)

We break "what gets valued and what doesn't" into four parts, then cover how to choose a project and estimate its size. Finally, you decide up front what you won't build and trim the project down to a size you can actually finish.

1

What This Course Can and Can't Tell You

We start by deciding not to include numbers without a source. We list four things you can verify and actually check a README mechanically.

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2

Breaking "Valued" Into Four Parts

It works, traces of judgment, commit history, awareness of operations. We restate the column's four points in a form you can check yourself.

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3

Choosing a Project (One Thing You Use Every Week)

Narrow the criteria to three: you use it, you can prepare the data yourself, and you can explain it in one screen.

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4

Estimating Size (Split Into Tasks, Then Convert to Time)

Give a range, not a single number. Split into tasks, add them up, and divide by your available hours per week to get weeks.

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5

Decide What You Won't Build First

Draw the scope line before you start and record it in the README as "known gaps," along with why you cut each thing.

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Chapter 2 — Finishing It (lessons 6–10)

We check how to set deadlines, commit history, the README, publishing, and recording improvements, using the output of a real repository. We finish by showing that the work is ongoing, with Issues and a week-by-week history.

6

Setting Deadlines (Slice Vertically)

Build layer by layer, or run one path all the way through? Same amount of work, but a different distance to "something you can show."

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7

You Can't Create Commit History After the Fact

We measure a bulk upload and a gradually built history side by side on the same project, looking at dates and message granularity.

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8

Test Your README on a Newcomer's Machine

It always works on the author's machine. We actually break it to see what happens when just one line is missing.

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9

Publishing (Have One URL People Can Open)

If it only runs on your machine, nobody can see it. Confirm it's published by the status and size you get back.

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10

Showing That It's Ongoing (Issues and a Weekly History)

Record what you want to fix as Issues, and show both the closed and open counts. Use a weekly history to show you keep working.

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Chapter 3 — Writing Your Work History (lessons 11–14)

We cover the skeleton of a work history document (shokumu keirekisho) and where to draw the line between what you can and can't put in numbers. We measure what decides how GitHub displays your work, and end with how to write about a period of self-study.

11

The Skeleton of a Work History Document

There's no fixed format. Assign the common essentials, "when, what, and how," to five fields and fill them in.

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12

What You Can and Can't Put in Numbers

Sort into three: verifiable now, writable once measured, and not verifiable by you. Measure before you write "made it faster."

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13

What Decides How GitHub Displays Your Work

The language bar is based on byte counts, and the description and topics stay empty unless you fill them in. We count to confirm.

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14

Self-Study Periods and How to Write About Getting Stuck

Use where you got stuck and how you got unstuck as material. You can dig up your own sticking points from your git history.

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Chapter 4 — The Hiring Process (lessons 15–18)

We look at coding test formats and actually solve practice problems to check time complexity and edge cases. We also cover a pattern for explaining your own code in a technical interview and how to prepare questions to ask the interviewer.

15

What Coding Tests Look At

Formats vary by company. Prepare by focusing on three things you can check in common: edge cases, input/output, and explanation.

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16

Solve Practice Problems and Measure Complexity

We actually run two practice problems: nested loops vs. a dictionary, and bracket matching that simple counting won't pass.

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17

Explaining Your Own Code in a Technical Interview

You don't need to remember it. Dig it up from your history and build a pattern for talking through it in four steps.

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18

Build Your Questions for the Interviewer From What You Can Verify

Look up what you can look up beforehand. Keep only what you can't learn without asking, and confirm terms in writing.

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Chapter 5 — After You Join (lessons 19–20)

We measure, on a 1,310-file repository, the steps for reaching the line you're looking for in an unfamiliar codebase. We finish with a system for continuing to learn and a wrap-up of all 20 lessons.

19

The First Three Months (Finding One Line Among 1,310 Files)

Don't read everything. We measure the steps of tracing from the entry point on a real repository. Ship small and check early.

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20

A System for Continuing to Learn, and a Wrap-Up of All 20 Lessons

Measure your system for keeping going with a weekly history. Look back on the five chapters and decide your next step.

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Once you've finished all 20 lessons, move on to Intro to Shipping and Running a Service to strengthen where and how you host your work, Algorithms for Beginners to keep preparing for tests, or Git & GitHub for Beginners to sharpen how you leave a history. A membership unlocks every course.