Applied AICollège Unica
5.4SpecializationSession 5 · Capstone Studio & Industry Deployment

Search engines and recommendation systems

15classes45htotalTH1 · PR2 · PNW2weighting per class

Class-by-class breakdown

15 classes

TH = theory · PR = practical · PNW = personal work. These are ministry weighting codes (not hours) used to split each class's minutes. Class length = course hours ÷ class count; the three time-boxes below always sum to that length.

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Quiz progress

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First 2 classes free with a referral 14 more with enrollment180 min per classTheory 36mPractical 72mPersonal Work 72m
1

From Keywords to Meaning — Agentic Search With GenAI

FreeTH1PR2PNW2

A Digital Marketing Strategist who understands how modern search matches meaning, not just keywords, writes content that gets found — semantic search is the new relevance.

Theory36m
  • What information retrieval is and how GenAI changed it (meaning vs keywords)
  • Embeddings and semantic similarity at a concept level
  • The retrieval problem: a query, a corpus, and the right result — now by meaning
Practical72m
  • Frame a sample e-commerce search as a semantic retrieval problem
  • List 3 business questions agentic search answers for an online store
Personal Work72m
  • Write a one-page agentic-search brief for a sample store
  • Micro-task: submit your brief
2

Embeddings and Vector Search — Finding by Meaning

LockedTH1PR2PNW2

Locked class preview

An E-commerce Director whose search returns 'running shoes' for 'sneakers' because embeddings match meaning sells more — vector search is the engine of modern discovery

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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3

RAG as Search — Retrieving Grounded Answers

LockedTH1PR2PNW2

Locked class preview

A Data/Business Analyst who builds RAG retrieval answers 'which of our products fits X?' from real catalog data instead of guessing — RAG is search that grounds the answer

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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4

Conversational Search — Asking Follow-Up Questions

LockedTH1PR2PNW2

Locked class preview

A Sales and Marketing Manager whose search lets a user ask 'show me something cheaper' as a follow-up sells more — conversational search keeps the user's context

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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5

Query Understanding With LLMs — What Did the User Mean?

LockedTH1PR2PNW2

Locked class preview

A Digital Marketing Strategist who uses an LLM to rewrite vague queries ('something comfy for work') into precise ones gets better results — LLM query understanding reads intent

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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6

Hybrid Search — Combining Keywords and Meaning

LockedTH1PR2PNW2

Locked class preview

A Data/Business Analyst who combines keyword and semantic search gets both precision and recall — hybrid search is the real-world default for product search

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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7

What Are Recommender Agents? — Suggesting the Next Thing

LockedTH1PR2PNW2

Locked class preview

An E-commerce Director who understands recommenders knows why 'customers also bought' drives major revenue — GenAI now powers richer, conversational recommendations

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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8

Collaborative Filtering — 'People Like You Also Bought'

LockedTH1PR2PNW2

Locked class preview

A Sales and Marketing Manager who uses collaborative filtering leverages real behavior — 'users who liked this also liked' is pure social proof GenAI can explain

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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9

Content-Based and Semantic Recommendations — Similar by Meaning

LockedTH1PR2PNW2

Locked class preview

A Data/Business Analyst who recommends by semantic similarity solves cold-start for new users and niche items — content-based + embeddings recommend by what things are

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10

LLM-Powered Recommendations — Explaining and Personalizing

LockedTH1PR2PNW2

Locked class preview

A Digital Marketing Strategist whose recommender explains 'because you liked X, you might like Y for these reasons' builds trust — GenAI makes recommendations understandable

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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11

Evaluating Search and Recs — Measuring Discovery Quality

LockedTH1PR2PNW2

Locked class preview

A Data/Business Analyst who measures search and recs with real metrics knows when a change actually helped — offline evals prevent bad launches

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12

Business Rules and Merchandising — Editorial Control With GenAI

LockedTH1PR2PNW2

Locked class preview

An E-commerce Director who adds business rules on top of GenAI search promotes margins and inventory — pure ML ignores what the business needs

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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13

Discovery Agents — Search and Recs as One Conversation

LockedTH1PR2PNW2

Locked class preview

A Project Manager who blends search and recommendations into one agent builds a discovery experience — 'search + suggested for you' is how modern stores guide users

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14

Bias and Safety in Discovery — Avoiding Echo Chambers

LockedTH1PR2PNW2

Locked class preview

An AI Integration Manager who ignores recommender bias ships filter bubbles and popularity bias — ethical discovery design keeps recommendation healthy and fair

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15

Mini-Project — A Discovery Agent for a Real Store

LockedTH1PR2PNW2

Locked class preview

This capstone rehearsal proves a Data/Business Analyst can build a working agentic search + recommendation demo that a real store could deploy

Enroll to unlock every class in this course — the full agenda, the AI tutor, and the quiz.

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Previous course

5.3 · Data mining techniques and analysis of textual and social network data

Next course

5.5 · Supervised project/internship

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