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no. 04 — 6 months · 16 modules

Data Science & Applied AI

syllabus — 6 months · 16 modules

Syllabus.

Sygjerime

phase 01 — months 1–4

Data Science.

approximate syllabus — the final plan is set by the tutor

  • Syntax
  • Functions
  • Collections
  • Classes Basics
  • Environments

  • NumPy
  • Pandas
  • Cleaning
  • Transformations

  • Querying
  • Joins
  • Aggregation
  • Relational Concepts

  • Matplotlib / Plotly
  • Dashboards
  • Explaining Data

  • Distributions
  • Probability
  • Correlation
  • Confidence
  • Hypothesis Testing

  • Regression
  • Classification
  • Clustering

  • Train/Test Split
  • Precision
  • Recall
  • F1
  • Overfitting

  • Real Datasets
  • Business Problems

phase 02 — months 5–6

AI Engineering.

llms → apis → prompting → structured outputs → embeddings → vector search → rag → evaluation → agents → deployment

week 1

  • Models
  • APIs
  • Prompting
  • Structured Outputs

week 2

  • Images / Docs
  • Function Calling
  • Python Tools

week 3

  • Embeddings
  • Semantic Search
  • Vector DBs

week 4

  • Chunking
  • Retrieval
  • Citations
  • Knowledge Assistants

week 5

  • Reranking
  • Hybrid Search
  • LLM-as-Judge

week 6

  • Tools
  • Memory
  • Planning
  • Agent Workflows

week 7

  • Agent SDKs
  • Orchestration
  • MCP
  • Multi-Agent Basics

week 8

  • FastAPI
  • Docker
  • Deployment
  • Monitoring
  • Final Project