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Kecerdasan Buatan Kelas B
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General
Pengumuman
Pengumuman
01 - AI Development Life Cycle
[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
AI-DLC Forum
Tugas 01A - Individual - Tahapan AI Development Life Cycle
Tugas 01B - Kelompok - Tahapan AI Development Life Cycle
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] Ashoka: Alat Skrining Kesehatan Organ Kelamin Anak berbasis Artificial Intelligence
[PRESENSI][VIDEO] ViuMe: Digital Pathology Platform Berbasis Artificial Intelligence
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
[PRESENSI][VIDEO] M02-1: Lists and Tuples
[PRESENSI][VIDEO] M02-2: Dictionaries
[PRESENSI][VIDEO] M02-3: Sets
[PRESENSI][Hands-On] Data Extraction and Best Practice AI/ML Engineering
[PRESENSI][TOOL] Google Colab: Cloud-based Jupyter Notebook by Google
[PRESENSI][TUTORIAL] Python Data Structures
[PRESENSI][TUTORIAL] Python Basics
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
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
[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
[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
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
[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
08 - Mid Exam (UTS)
[PRESENSI] Mid Exam - Part 1
[PRESENSI] Mid Exam - Part 2
[PRESENSI] Mid Exam - Part 1
[PRESENSI] Mid Exam - Part 2
09 - Modeling Evaluation 1
[PRESENSI] Hold-Out to K-Fold
[PRESENSI] Cross-Validation
[PRESENSI] Evaluation Metrics
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
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
[PRESENSI][VIDEO] Module 16-1: Introduction to Logistic Regression
[PRESENSI][VIDEO] Module 16-2: Training a Logistic Regression Model
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
[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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Course information
Kecerdasan Buatan Kelas B
Teacher:
531141113025 Nova Eka Diana
Teacher:
531141113025 nova eka diana
Synchronous Meeting Type
:
Blended (Online and Face-to-Face)
Skill Level
:
Beginner
