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    Umum
    Pengumuman
    RPS: Rencana Pembelajaran Semester - AI 2025/2026
    Stage 1: Business Understanding
    Stage 2: Data Understanding and Data Preparation
    Stage 3: Modeling and Evaluation
    Stage 4: Final Presentation
    Stage 5: Final Report
    01 - AI Development Life Cycle
    AI-DLC Forum
    [PRESENSI][VIDEO] Course Introduction and AI Development Life Cycle
    [PRESENSI] Rencana Pembelajaran Semester (RPS)
    [PRESENSI] SKKNI AI - Data Science
    [PRESENSI][SLIDE] Course Introduction
    [PRESENSI][SLIDE] AI Development Life Cycle
    Tugas 01A - Individual - Tahapan AI Development Life Cycle
    Tugas 01B - Kelompok - Tahapan AI Development Life Cycle
    Practice Quiz 1
    02 - Business Understanding
    [PRESENSI][VIDEO] Client Interview 1: ViuMe Project (Dr. dr. Nunung Ainur Rahmah, Sp.PA. - FK Yarsi / RS Yarsi)
    [PRESENSI][VIDEO] Client Interview 2 - PRISM Project (dr. Astari Arum Sari, SpAn. - RS Yarsi)
    [PRESENSI][VIDEO] Client Interview 3 - SenusaBio Project (Fitrah Nur Rabbany - Pandu Group)
    [PRESENSI][VIDEO] Client Interview 4 - Ashoka Project (dr. Reyner Arden - FKUI / RSCM)
    [PRESENSI][VIDEO] ViuMe: Digital Pathology Platform Berbasis Artificial Intelligence
    [PRESENSI][VIDEO][EXTERNAL] AI to Predict Sepsis in ICU
    [PRESENSI][VIDEO] SenusaBio: AI-Based Genomic Variant Interpretation for Healthcare Services
    [PRESENSI][VIDEO] Ashoka: Alat Skrining Kesehatan Organ Kelamin Anak berbasis Artificial Intelligence
    [PRESENSI][PAPER] SenusaBio: Utomo et al. 2024 - A Novel Feature Representation Method for Automating Genetic Variant Classification
    [PRESENSI][PAPER] PRISM: Utomo et al. 2024 - Scalable Personalized Treatment Recommendation
    [PRESENSI][PAPER] ViuMe: Utomo et al. 2025 - Optimizing Image Processing for AI-Driven Cervical Cancer Diagnosis
    [PRESENSI][PAPER] Ashoka: Circapproved Digital Pattern Recognition via ANN for the Identification of Normal Penis
    Practice Quiz 2
    03 - Data Understanding 1: Data Visualization
    [PRESENSI][VIDEO] M01-1A: Introduction to Python
    [PRESENSI][VIDEO] M01-1B: Getting Started with Jupyter Notebook
    [PRESENSI][VIDEO] M01-2: Types
    [PRESENSI][VIDEO] M01-3: Expression and Variables
    [PRESENSI][VIDEO] M01-4: String Operations
    [LAB][PRAKTIKUM] Module 01 - Python Basic
    Practice Quiz Module 01 - Python Basics
    [PRESENSI][VIDEO] M02-1: Lists and Tuples
    [PRESENSI][VIDEO] M02-2: Dictionaries
    [PRESENSI][VIDEO] M02-3: Sets
    [LAB][PRAKTIKUM] Module 02 - Python Data Structures
    Practice Quiz Module 02 - Python Data Structure
    [PRESENSI][Hands-On] Data Extraction and Best Practice AI/ML Engineering
    [PRESENSI][TOOL] Google Colab: Cloud-based Jupyter Notebook by Google
    [PRESENSI][TUTORIAL] Python Basics
    [PRESENSI][TUTORIAL] Python Data Structures
    04 - Data Understanding 2: Statistical Analysis
    [PRESENSI][VIDEO] M03-1: Conditions and Branching
    [PRESENSI][VIDEO] M03-2: Loops
    [PRESENSI][VIDEO] M03-3: Functions
    [PRESENSI][VIDEO] M03-4: Exception Handling
    [PRESENSI][VIDEO] M03-5: Objects and Classes
    [LAB][PRAKTIKUM] Module 03 - Python Programming Fundamentals
    Practice Quiz Module 03 - Python Programming Fundamentals
    [PRESENSI][VIDEO] M04-1A: Reading Files with Open
    [PRESENSI][VIDEO] M04-1B: Writing Files with Open
    [PRESENSI][VIDEO] M04-2A: Pandas Loading Data
    [PRESENSI][VIDEO] M04-2B: Pandas Working with Saving Data
    [PRESENSI][VIDEO] M04-3A: One Dimensional Numpy
    [PRESENSI][VIDEO] M04-3B: Two Dimensional Numpy
    [LAB][PRAKTIKUM] Module 04 - Working with Data in Python
    Practice Quiz Module 04 - Working with Data in Python
    [PRESENSI][Hands-On] Data Exploration
    [PRESENSI][TUTORIAL] Pandas
    [PRESENSI][TUTORIAL] Numpy
    [PRESENSI][TUTORIAL] Python Control Flow (Conditions, Loops, and Functions)
    [PRESENSI][TUTORIAL] Python Exception Handling
    [PRESENSI][TUTORIAL] Python Objects and Classes
    [PRESENSI][TUTORIAL] Python Input and Output
    05 - Data Understanding 3: Exploratory Data Analysis (EDA) Report
    [PRESENSI][VIDEO] M05-1: Exploratory Data Analysis
    [PRESENSI][VIDEO] M05-2: Descriptive Analytics
    [PRESENSI][VIDEO] M05-3: GroupBy in Python
    [PRESENSI][VIDEO] M05-4: Correlation
    [PRESENSI][VIDEO] M05-5: Correlation Statistics
    Practice Quiz Module 5 - Exploratory Data Analysis
    [PRESENSI][VIDEO] M06-1: Overview of Data Visualization
    [PRESENSI][VIDEO] M06-2: Types of Plots
    [PRESENSI][VIDEO] M06-3: Plot Libraries
    [PRESENSI][VIDEO] M06-4: Introduction to Matplotlib
    [PRESENSI][VIDEO] M06-5: Basic Plotting with Matplotlib
    [PRESENSI][VIDEO] M06-6: Dataset on Immigration to Canada
    [PRESENSI][VIDEO] M06-7: Line Plots
    Practice Quiz Module 6 - Data Visualization
    Tugas Lab 5 - Exploratory Data Analysis (EDA)
    06 - Data Preparation 1: Handling Data Problems
    [PRESENSI][VIDEO] M07-1: Area Plots
    [PRESENSI][VIDEO] M07-2: Histogram
    [PRESENSI][VIDEO] M07-3: Bar Charts
    [PRESENSI][VIDEO] M07-4: Pie Charts
    [PRESENSI][VIDEO] M07-5: Box Plots
    [PRESENSI][VIDEO] M07-6: Scatter Plots
    [PRESENSI][VIDEO] M07-7: Plotting Directly with Matplotlib
    Practice Quiz Module 07 - Basic and Specialized Visualization Tools
    [PRESENSI][VIDEO] M08-1: Dashboarding Overview
    [PRESENSI][VIDEO] M08-2: Introduction to Plotly
    [PRESENSI][VIDEO] M08-3: Introduction to Dash
    [PRESENSI][VIDEO] M08-4: Make Dashboards Interactive
    07 - Data Preparation 2: Feature Engineering
    [PRESENSI][VIDEO] M09-1: Pre-processing Data in Python
    [PRESENSI][VIDEO] M09-2: Dealing with Missing Values in Python
    [PRESENSI][VIDEO] M09-3: Data Formatting in Python
    [PRESENSI][VIDEO] M09-4: Data Normalization in Python
    [PRESENSI][VIDEO] M09-5: Binning in Python
    [PRESENSI][VIDEO] M09-6: Turning Categorical Variables into Quantitative Variables
    Practice Quiz Module 09 - Data Wrangling
    [PRESENSI][SLIDE] AI for NLP - Case Study: Classification of Medical Specialization
    [Lab][Code] AI for NLP - Case Study: Classification of Medical Specialization
    08 - Mid Exam (UTS)
    [PRESENSI] Mid Exam - Part 1
    [PRESENSI] Mid Exam - Part 2
    09 - Modeling Evaluation 1
    [PRESENSI][SLIDE] AI for Computer Vision - Case Study: Monkey Pox Diagnosis
    [LAB][CODE] AI for Computer Vision - Case Study: Monkey Pox Diagnosis
    [PRESENSI][CODE] AI for Time Series Analytics - Case Study: Sepsis Prediction
    10 - Modeling Evaluation 2
    [PRESENSI][VIDEO] Module 13-1: Classification Metrics and Evaluation Techniques
    [PRESENSI][VIDEO] Module 13-2: Regression Metrics and Evaluation Techniques
    [PRESENSI][VIDEO] Module 13-3: Evaluating Unsupervised Learning Models
    Practice Quiz Module 13 - Evaluating Machine Learning Models
    [PRESENSI][VIDEO] Module 14-1: Cross Validation and Advanced Model Validation Tehniques
    [PRESENSI][VIDEO] Module 14-2: Regularization in Regression and Classificaiton
    [PRESENSI][VIDEO] Module 14-3: Data Leakage and Other Pitfalls
    Practice Quiz Module 14 - Best Practices for Ensuring Model Generalizability
    11 - Modeling 1: Fundamental Models
    [PRESENSI][VIDEO] Module 15-1: Introduction to Regression
    [PRESENSI][VIDEO] Module 15-2: Introduction to Simple Linear Regression
    [PRESENSI][VIDEO] Module 15-3: Introduction to Multiple Linear Regression
    [PRESENSI][VIDEO] Module 15-4: Polynomial and Non-Linear Regression
    Practice Quiz Module 15 - Linear Regression
    [PRESENSI][VIDEO] Module 16-1: Introduction to Logistic Regression
    [PRESENSI][VIDEO] Module 16-2: Training a Logistic Regression Model
    Practice Quiz Module 16 - Logistic Regression
    12 - Modeling 2: Model Improvements
    [PRESENSI][VIDEO] Module 17-1: Classification
    [PRESENSI][VIDEO] Module 17-2: Decision Trees
    [PRESENSI][VIDEO] Module 17-3: Regression Trees
    Practice Quiz Module 17 - Decision and Regression Trees
    [PRESENSI][VIDEO] Module18-1: Support Vector Machines (SVMs)
    [PRESENSI][VIDEO] Module 18-2: K-Nearest Neighbors (KNNs)
    [PRESENSI][VIDEO] Module 18-3: Bias, Variance and Ensemble Models
    13 - Modeling 3: Model Implementation
    [PRESENSI][VIDEO] Module 19-1: Clustering Strategies and Real-World Application
    [PRESENSI][VIDEO] Module 19-2: K-Means Clustering
    [PRESENSI][VIDEO] Module 19-3: DBScan and HDBScan Clustering
    [PRESENSI][VIDEO] Module 20-1: Clustering Dimention Reduction and Feature Engineering
    [PRESENSI][VIDEO] Module 20-2: Dimension Reduction Algorithm
    14 - AI Project Management
    [PRESENSI][VIDEO] Sustainability & Responsibility: Manajemen Proyek AI Melampaui Kode Program
    [PRESENSI][VIDEO] Audit Kode dan Tata Kelola AI: Menghindari 'Technical Debt' dalam Proyek Akhir
    15 - Project Presentation
    [PRESENSI][VIDEO] Professional Presentation for AI Development: Model Aristotelian dalam Manajemen Proyek
    [PRESENSI][VIDEO] Translating AI Solutions: Praktik Presentasi Proyek untuk Pemangku Kepentingan
    16 - Final Exam (UAS)
    Kisi-Kisi UAS
    [PRESENSI] Final Exam
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    Kecerdasan Buatan Kelas A

    • Pengajar: 1402023005 Ahmad Fauzi Ramadhan
    • Pengajar: 531141112024 Chandra Prasetyo Utomo
    • Pengajar: 1402023020 Dina Amaliah
    • Pengajar: 1402023032 Luthfi Paundra Aunurrahman
    • Pengajar: 5311411120243 Mufid Farhan Muhana
    • Pengajar: 1402023044 Muhammad Rizal Anditama Nugraha
    • Pengajar: 5311411120242 Muhammad Wildan Pratama
    • Pengajar: 1402023045 Muhammad Yusuf Al Ghifari
    • Pengajar: 5311411120241 Nashuha Insani
    • Pengajar: 531141113025 Nova Eka Diana
    • Pengajar: 531141113025 nova eka diana
    • Pengajar: 1402023067 Sultan Hafidzh Polihito
    Synchronous Meeting Type: Blended (Online and Face-to-Face)
    Skill Level: Beginner

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