Akdeniz University · Computer Engineering (English) · Semester 7
An open study archive for this course. A week-by-week plan following the 2026-2027 instructor's roadmap, the instructor's slides, project brief and starter code, the official syllabus topics, and a completed term project from a previous student.
Instructor (Fall 2026-2027): Dr. Alper Özcan · Course communication on Microsoft Teams
The 2026-2027 course is BIST 100 financial analytics with Python and MCP AI
agents: market data → indicators → support/resistance → backtest → AI agent. The
official syllabus's economics topics are kept in
syllabus-topics.md as written-exam background.
| Component | Count | Weight |
|---|---|---|
| Midterm | 1 | 20% |
| Quiz | 1 | 10% |
| Term project | 1 | 30% |
| Final | 1 | 40% |
Midterm: written exam covering core concepts · Quiz: short checks for weekly learning · Project: must be implemented in Python · Final: comprehensive.
Integrated BIST 100 Agentic Financial Analytics Harness — project brief (Dr. Alper Özcan).
- Due November 24, 2026, 23:59 on Teams (multiple submissions allowed).
- Proposal + final report; groups of two are allowed; Python.
- Build an educational analysis system for a 30-stock BIST 100 universe that combines deterministic Python tools, multiple evidence sources, backtest verification and a controlled MCP AI-agent workflow — not a single prediction model.
- Four mandatory research scenarios: sector laggard / catch-up, weekday and multi-day patterns, technical reversal events, quarterly fundamentals and price reaction.
- LLM reasons and explains. Python tools calculate. The harness controls. Backtests verify. Evidence is logged. A human makes the final decision. Strictly educational: no broker connection, no real orders, no investment advice.
- Starter code:
scenario2_thyao_weekday_patterns.py,scenario3_technical_reversal_events_3_periods.py. - A previous student's stock technical-analysis project:
assignments/undated-term-project/.
From the instructor's roadmap in the week 1 slides.
| # | Topic | Note |
|---|---|---|
| 1 | BIST 100 and Yahoo Finance | weeks/01 |
| 2 | Algorithmic Trading and the Agentic Harness | weeks/02 |
| 3 | Technical Indicators | weeks/03 |
| 4 | Backtesting Strategies | weeks/04 |
| 5 | Time Series with Pandas | weeks/05 |
| 6 | Lab: BIST Data | weeks/06 |
| 7 | Lab: Support and Resistance | weeks/07 |
| 8 | Midterm | weeks/08 |
| 9 | Engineering Economics Concepts | weeks/09 |
| 10 | Fundamental Analysis and Valuation | weeks/10 |
| 11 | Money Management | weeks/11 |
| 12 | MCP AI Agent | weeks/12 |
| 13 | Project Presentations I | weeks/13 |
| 14 | Project Presentations II | weeks/14 |
1. Open the week you are on in weeks/: goals, key concepts from the
slides, readings, and a practice list with the code to run.
2. Run the code. Everything in this course is Python — pip install yfinance pandas matplotlib in a virtual environment and reproduce the slide examples.
3. Start the project early — it is 30%, more than the midterm, and due November 24.
4. For the written exams, the official economics topics are in
syllabus-topics.md with book links at the exact page.
5. Write under your own ## Notes — <Name> (<term>) section at the bottom of each week note — see Taking notes.
Two openly licensed textbooks are in this repository; every reading link in
syllabus-topics.md opens one of them at the exact page.
| Book | Covers | Licence |
|---|---|---|
| OpenStax, Principles of Economics 3e — 995 pp. | Syllabus topics 1-11 | CC BY-NC-SA 4.0 |
| Schmid & Vanderby, Engineering Economics — 254 pp. | Syllabus topics 12-14, week 9 | CC BY 4.0 |
Neither is the syllabus's cited book, but between them they cover the whole course: OpenStax follows the same micro-then-macro path as Mankiw, and Schmid & Vanderby covers the time value of money and project evaluation that Chan S. Park does.
Also cited by the syllabus, not here: Mankiw Principles of Economics / Principles of Macroeconomics, Chan S. Park Fundamentals of Engineering Economics, Okka Mühendislik Ekonomisine Giriş (TR), Samuelson & Nordhaus Economics.
Statistics: TÜİK, Eurostat, OECD.
README.md This page
course-info.md Resource map (books, syllabus topic → chapter), Turkish ↔ English glossary
syllabus-topics.md The official syllabus's 14 economics topics, with book links
weeks/NN-*.md One file per week: the shared plan on top, everyone's notes below
exams/ Past papers (none collected yet) and how to add one
resources/ Syllabus PDF, books/, 2026-2027-fall/ (slides, project brief, papers/, code/)
assignments/ Term projects and other own work — including a previous student's project
Open the week, scroll to the bottom, write under your own heading:
## Notes — <Name> (<term>)
### Lecture
### Code
### Questions
### Exam-worthyAdd your heading below the existing ones and never edit someone else's section — different sections merge in git without conflicts.
| What | Who edits it | When |
|---|---|---|
Top of weeks/NN-*.md and syllabus-topics.md |
anyone | Only when the course itself changes — a new topic, a better reading, a correction. |
## Notes — <you> in a week file |
only you | Every week. This is your notebook. |
course-info.md, exams/README.md |
anyone | When you learn something durable: a new exam pattern, a better source. |
assignments/<term>-<you>/ |
only you | Your assignments, projects, submissions. |
resources/<term>/ |
anyone in that term | Slides, syllabus and lab sheets the instructor issued. |
exams/ |
anyone | When you get hold of a new paper — blank or answered. Put the writer's surname in the filename (2026-2027-final-answered-<surname>.pdf). Exam papers never go under assignments/. |
Two students in different years never touch the same file except to improve the shared plan — which is the point.
Add your term to the table below with the instructor and dates, write your notes in
the week files, and put your project under assignments/<term>-<you>/. Keep the
shared plan in weeks/ and course-info.md general.
Use a lowercase, hyphenated name in folder names — efe-kurucay, not Efe Kuruçay.
Previous students' work is here as reference, not to hand in.
| Term | Instructor | Schedule | Midterm | Final | Notes |
|---|---|---|---|---|---|
| Fall 2026-2027 | Dr. Alper Özcan | TBD | Week 8 | TBD | Slides, project brief, papers and starter code in resources/2026-2027-fall/; project due Nov 24, 2026; Efe — in every week file |
| Undated | — | — | — | — | A completed term project by a previous student: assignments/undated-term-project/ |
Grading in Fall 2026-2027: Midterm 20% · Quiz 10% · Project 30% · Final 40%.