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Course Description
In this course, students focus on learning to apply the concept of acquisition/retrieval of various kinds of data from various sources and teach about the application of artificial intelligence methods, namely techniques for making machines/computers smart. So that machines and computers are able to think and make decisions like humans when acting. Apart from that, this course teaches about the application of artificial intelligence methods, starting from knowledge representation, search methods, language computing, Single-Layer Perceptron (Forward and Backpropagation), Loss Function & Gradient Descent, and MultiLayer Forward Propagation. Students also study the creation and development of artificial intelligence-based algorithms in solving multidisciplinary problems which will ultimately produce innovative work that is tested using the case study learning model.
Program Objectives (PO)
- 1. Menguasai konsep teoritis arsitektur, infrastruktur, metode pemrosesan, dan manajemen data, teknologi data besar serta mampu memformulasikan penyelesaian masalah data secara tepat.
- 2. Menguasai konsep teoritis algoritma kecerdasaan buatan, pembelajaran mesin dan komputasi cerdas, serta mampu memformulasikan penyelesaian masalah di big data sesuai problem domain dengan algoritma yang terbaik
- 3. Mampu membuat model komputasi untuk mendukung pengambilan keputusan dengan menerapkan algoritma kecerdasaan buatan secara mandiri maupun berkelompok dengan penuh rasa tanggung jawab
- 4. Mampu menerapkan metode tuning parameter dalam rangka menghasilkan kualitas luaran terbaik secara mandiri dengan penuh rasa tanggung jawab
Aktifitas Pembelajaran
-
Pertemuan 1 Pengertian, Fenomena kemunculan, Sifat-sifat, Kompleksitas, dan Framework Big data serta memahami motivasi atau latar belakang teknik dasar dan metode kecerdasan mesin -
Pertemuan 2 Dan mengimplementasikan pemrograman R serta mengenaltools MapReduce -
Pertemuan 3 Dan mengimplementasikan pemrograman R serta mengenaltools MapReduce -
Pertemuan 4 Review pemrograman R, pengenalan tools MapReduce -
Pertemuan 5 Cara Pre-processing data dan visualisasi data -
Pertemuan 6 Melakukan analisis Data Structured, Analisis Data Unstructured, dan Analisis Text -
Pertemuan 7 Melakukan analisis Data Structured, Analisis Data Unstructured, dan Analisis Text -
Pertemuan 8 Melakukan analisis Data Structured, Analisis Data Unstructured, dan Analisis Text -
Pertemuan 9 Teknik-teknik dalam kecerdasan buatan -
Pertemuan 10 Evolutionary: Algoritma Genetika case in Searching, (Blind search dan inform search) -
Pertemuan 11 Evolutionary: Algoritma Genetika case in Searching (Fuzzy System) -
Pertemuan 12 Evolutionary: Algoritma Genetika case in Searching (Fuzzy System) -
Pertemuan 13 Evolutionary: Algoritma Genetika case in Learning ( Decision Tree Learning dan Jaringan Syaraf Tiruan) -
Pertemuan 14 Evolutionary: Algoritma Genetika case in Learning ( Decision Tree Learning dan Jaringan Syaraf Tiruan) -
Pertemuan 15 Evolutionary: Algoritma Genetika case in Learning ( Decision Tree Learning dan Jaringan Syaraf Tiruan) -
Pertemuan 16 Evolutionary: Algoritma Genetika case in Learning ( Decision Tree Learning dan Jaringan Syaraf Tiruan)
References
- Bernard Marr, Data Strategy: How to Profit from a World of Big Data, Analytics and Artificial Intelligence, 2018
- Medical Informatics: Concepts, Methodologies, Tools, and Applications; Joseph Tan; Wayne State University, USA, 2009.
- Obesity Prediction Approach Based Habit Parameter and Clinical Variable Using Self Organizing Map, Lilik Anifah, International Conference on Electronics, Biomedical Engineering, and Health Informatics, Springer Nature Singapore, 2023
Lecturer
Difficult Things About Education.
$75$10
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