Berlian Sistem Informasi - LLM Bootcamp
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Fahmi Iman Alfarizki

Berlian Sistem Informasi - LLM Bootcamp

Fahmi Iman Alfarizki
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Kurikulum Course

  • 1

    Chapter 1 (00:00)

    • Pre Test Chapter 1

    • Sesi 1 - Introduction to Database and SQL

    • Assignment Sesi 1

    • Sesi 2 - Basic Query, Aggregate Functions & Grouping Data

    • Assignment Sesi 2

    • Sesi 3 - Joins, Subqueries, and Nested Queries

    • Assignment Sesi 3

    • Post Test Chapter 1
  • 2

    Chapter 2 (00:00)

    • Pre Test Chapter 2

    • Sesi 4 - Python Basic Syntax, Data Types & Operator

    • Assignment sesi 4

    • Sesi 5 - Python Control Flow

    • Assignment Sesi 5

    • Sesi 6 - Python Functions, Package & Module

    • Assignment Sesi 6

    • Sesi 7 - Python Object-Oriented Programming (OOP)

    • Assignment Sesi 7

    • Sesi 8 - API using FastAPI and REST API

    • Assignment Sesi 8

    • Sesi 9 - Pandas: Data Cleaning and Preparation

    • Assignment Sesi 9

    • Sesi 10 - Pandas: Exploratory Data Analysis

    • Assignment Sesi 10

    • Sesi 11 - Data Visualization using Matplotlib and Seaborn

    • Assignment Sesi 11

    • Sesi 12 - Practical Descriptive Statistics

    • Assignment Sesi 12

    • Sesi 13 - Practical Inferential Statistics

    • Assignment Sesi 13

    • Sesi 14 - Mini Project 1: Statistical Analysis using Python

    • Post Test Chapter 2
  • 3

    Chapter 3 (00:00)

    • Pre Test Chapter 3

    • Sesi 15 - Introduction to Machine Learning

    • Assignment Sesi 15

    • Sesi 16 - Feature Engineering Part 1

    • Assignment Sesi 16

    • Sesi 17 - Feature Engineering Part 2

    • Assignment Sesi 17

    • Sesi 18 - Regularization and Classification

    • Assignment Sesi 18

    • Sesi 19 - Decision Tree, Ensemble Learning, and Hyperparameter Tuning

    • Assignment Sesi 19

    • Sesi 20 - Unsupervised Learning: PCA & Clustering

    • Assignment Sesi 20

    • Sesi 21 - Introduction to Deep Learning and Artificial Neural Network

    • Assignment Sesi 21

    • Sesi 22 - Mini Project 2: End to End Machine Learning Project

    • Post Test Chapter 3
  • 4

    Chapter 4 (00:00)

    • Pre Test Chapter 4

    • Sesi 23 - LLM Foundation Model

    • Sesi 24 - Prompt Engineering Essentials

    • Sesi 25 - Prompt Optimization

    • Sesi 26 - LLM API Integration & Architecture

    • Sesi 27 - Mini Project 3: Prompt Optimization

    • Post Test Chapter 4
  • 5

    Chapter 5 (00:00)

    • Pre Test Chapter 5

    • Sesi 28 - Foundations of Embeddings & Vector Databases

    • Sesi 29 - Chunking, Metadata & Embedding Pipeline Implementation

    • Sesi 30 - RAG Architecture & Retrieval Strategies

    • Sesi 31 - RAG Optimization: Re-ranking, Caching & Scaling

    • Sesi 32 - LangChain

    • Sesi 33 - Mini Project 4: Build a Complete RAG System

    • Post Test Chapter 5
  • 6

    Chapter 6 (00:00)

    • Pre Test Chapter 6

    • Sesi 34 - Azure Cloud Platform Overview

    • Sesi 35 - Azure OpenAI and AI Search

    • Sesi 36 - Azure ML and AI Foundry

    • Final Project Announcement

    • Sesi 37 - Mini Project 5: Deploy AI System on Azure

    • Post Test Chapter 6
  • 7

    Chapter 7 (00:00)

    • Pre Test Chapter 7

    • Sesi 38 - LLM Evaluation Metrics, Safety and Toxicity Detection

    • Sesi 39 - Logging, Monitoring, and Analytics

    • Sesi 40 - A/B Testing for LLMs

    • Sesi 41 - Mini Project 6: LLM Monitoring Dashboard

    • Sesi 42 - Wrapping Up: AI Application Development & Deployment

    • Post Test Chapter 7

    • Sesi 43 - Final project completion and mentoring

    • Sesi 44 - Final project completion and mentoring

    • Sesi 45 - Final Project Presentation

Prasyarat

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Instructor

Fahmi Iman Alfarizki

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Sertifikat untuk Course ini

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