Blog · 15 September 2026

Second-year Bachaloria Programming notes: all 7 units on one page

A quick summary of the second-year Bachaloria Programming & AI curriculum: the main idea and key terms of each of the seven units, for revision after you have studied the book.

Before you start

These are revision notes, not a replacement for the ministry's textbook. Study the lesson first, then come back here to check you have the essentials. The summary is ours; for the exam, the reference is the book.

Unit 1: Information Technology and Society

  • Technology changed how we communicate, work and learn at every stage.
  • AI: a program that learns from examples instead of us writing its rules.
  • Its uses: recommendations, face recognition, and industry.
  • Its ethics: bias, privacy, transparency and accountability.

Unit 2: Cybersecurity

  • Encryption: symmetric (one key) and asymmetric (public and private).
  • Authentication: something you know, have, or are. Two together = two-factor authentication.
  • Network security: firewall, segmentation, least privilege, updates.
  • Incidents: detect, contain, remove the cause, recover, learn. Risk = likelihood × harm.

Full explainer

Unit 3: Web Applications

  • Three parts: frontend, server, database.
  • HTML structure, CSS appearance, JavaScript behaviour.
  • Request and response, and status codes: 200 fine, 404 not found, 500 a server problem.
  • HTTPS = the connection is encrypted.

Unit 4: Web Design and Media

  • Media: text, images, audio, video. Higher quality = bigger file.
  • User experience (UX): clarity, consistency, and feedback when you press something.
  • Evaluating websites: speed, ease of use, and accurate content.
  • Iterative improvement: build, test, fix, repeat.

Full explainer for units 3 and 4

Unit 5: Data Collection and Cleaning

  • Ways to collect: surveys, sensors, logs and existing sources.
  • Cleaning: remove duplicates, handle missing values, and standardise formats.
  • Open data: data published for anyone to use.
  • API: the way one program asks another for data.

Unit 6: Analysis and Communication

  • Statistical inference: judging the whole from a sample.
  • Regression: a relationship between two variables you can predict with, e.g. hours studied and marks.
  • Evaluation: how close the prediction is to reality.
  • Visual representation: the right chart for the idea, and an honest chart rather than a misleading one.

Unit 7: Machine Learning and AI

  • Kinds of learning: supervised, unsupervised and reinforcement.
  • Training and testing data, and overfitting.
  • Neural network: layers and weights adjusted by training. Deep learning = many layers.
  • Large language model: predicts the next word. Generative, and can be confidently wrong.

Full explainer

Want the teaching, not just the summary?

Eng. Ahmed Tarek teaches all seven units in order on the subject page, and his first five videos are free.

Sources

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