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CIS 5020: Critical Analysis of Algorithms
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Super Syllabus

The Algorithmic Landscape

20+ topics. 300+ pages. Your job: Discover what calls to you.

Not: Read all of it.

Is: Explore with Claude to find your curiosity.


Why We’re Not Summarizing It For You

Banking model approach: Pre-digest complexity → give you bite-sized chunks → tell you what’s important

Problem-posing approach: Give you the full landscape → teach you to navigate complexity → trust you to discover what matters

The skill: Not “read summaries.”

The skill: “I have complexity. I have Claude. How do I make sense of this?”

This is the actual transferable skill.

In your career, you’ll encounter:

  • 500-page technical specs
  • Competing research papers
  • Dense legal documents
  • Complex codebases

Learning to navigate complexity with a cognitive partner is the course in microcosm.


How to Explore

Your Assignment (Track 2)

  1. Upload all topic files to a Claude Project
  2. Spend 60-90 minutes exploring with Claude
  3. Save your conversation
  4. Submit:
    • Your top 7 ranked topics
    • 2-3 sentences explaining WHY each interests you
    • Your Claude conversation link
    • One thing you learned about HOW to use Claude for exploration

Deadline: Sunday, Feb 8, 11:59 PM


Exploration Modes

Before you ask Claude about topics, first ask:

“What am I trying to learn right now?”

Then pick your mode:

Mode 1: Broad Survey

Goal: Get the lay of the land

Prompt:

“Claude, I’m looking at the CIS 5020 super-syllabus. Give me a 2-3 sentence summary of each topic, focusing on what makes each one unique.”

When to use: Starting from zero knowledge


Mode 2: Connection Discovery

Goal: See how topics relate

Prompt:

“I’m interested in [topic A]. What other topics in this collection connect to it? How do they relate?”

When to use: You found something interesting, want to explore adjacent topics


Mode 3: Practical Grounding

Goal: Understand real-world relevance

Prompt:

“For each topic, give me one concrete real-world example of where this algorithmic lens matters.”

When to use: Topics feel too abstract, want to ground them in reality


Mode 4: Project Brainstorming

Goal: Imagine what you could build

Prompt:

“I’m thinking about doing a portfolio project on [topic]. What are 3-5 possible project directions I could explore?”

When to use: Thinking ahead to portfolio work


Mode 5: Curiosity Following

Goal: Discover interests you didn’t know you had

Prompt:

“I don’t know what interests me yet. Help me explore by asking me questions about what kinds of problems I find compelling.”

When to use: Genuinely unsure what calls to you


Mode 6: Deep Dive

Goal: Really understand one topic

Prompt:

“I want to understand [topic] more deeply. Walk me through the ‘Why This Matters’ section and help me see why someone would care about this.”

When to use: One topic caught your attention, want to go deeper


Mode 7: Contrast Comparison

Goal: Distinguish between similar topics

Prompt:

“What’s the difference between [topic A] and [topic B]? When would I use one lens vs. the other?”

When to use: Two topics seem similar, need to understand the distinction


If You Feel Overwhelmed

That’s normal. That’s banking model damage.

You’ve been trained to:

  • Avoid complexity
  • Wait for someone to tell you what’s important
  • Scroll past anything longer than a tweet

The solution isn’t to make it smaller.

The solution is to learn how to navigate complexity with a cognitive partner.

This is healing work.


Get the Materials

Browse Topics Online

All 21 algorithmic topics are available below. Click any topic to read the full document.

Download Full Package

Download ZIP

What’s in the ZIP:

  • All 20+ topic markdown files
  • This exploration guide (PDF)
  • Example Claude prompts

What You’re Learning

Beyond algorithmic topics, you’re learning:

  1. How to use Claude to navigate unfamiliar domains (transferable skill)
  2. How to recognize genuine vs. surface interest (self-knowledge)
  3. How to synthesize across multiple sources (information literacy)
  4. How to ask good exploratory questions (metacognition)
  5. How to build understanding through dialogue (epistemic AI use)

This is teaching you to think WITH AI, not outsource thinking TO AI.


Questions?

“60-90 minutes seems like a lot”

  • It’s an investment in shaping a course around YOUR interests
  • Most students find it engaging once they start

“What if I still don’t know after exploring?”

  • That’s valuable data. Submit your conversation anyway. We’ll talk.

“Can I explore with a partner?”

  • Yes, but each person submits their own rankings and reflection

“What if my interests change later?”

  • That’s expected. We’ll have checkpoints throughout the semester.