Data Professionals Competencies Petal Plot tau-data Indonesia

Kurikulum Tradisional Ilmu Data Berbasis Kompetensi

Dibawah ini adalah kurikulum sistem konvensional berbasis kompetensi. Pengguna sistem tau-data dianjurkan untuk menggunakan sistem kurikulum terbaru yang diproyeksikan saat telah lengkap nanti menjadi dasar penting sistem Pendidikan 4.0 di Link berikut ini.

Matematika ~ Statistika

  • Matematika Dasar
  • Analisa Algoritma & Struktur Data
  • Aljabar Linear & Optimasi
  • Metode Numerik
  • Statistika Dasar
  • General Linear Models.
  • Metode Penelitian.
  • Pendahuluan Teknik Sampling & Rancangan Percobaan.

Data Analyst

  • Pendahuluan Data Science dan Big Data (DSBD)
  • Pendahuluan Pemrograman Python
  • Pendahuluan Basis Data
  • Exploratory Data Analysis
  • Pendahuluan Data Mining
  • Pendahuluan Time Series analysis
  • Pendahuluan Spatial Analysis
  • Teknik sampling tingkat lanjut.
  • Pendahuluan Cloud Solutions.
  • Soft skills for Data Professional.
  • Data Ethics, Legals, and Privacy

Data Scientist

  • Teknik pemrograman dan Struktur Data tingkat lanjut.
  • Pemrograman Python Tingkat Lanjut.
  • Pendahuluan Deep Learning & Reinforcement learning.
  • Text Mining dan Natural language processing.
  • Social Media Analytics.
  • Signal processing (audio analysis)
  • Computer Vision.
  • Real-time Analytics
  • Data Science for Big Data
  • Bioinformatics.
  • Bayesian Learning Theory.
  • Big Data Framework Hadoop & Spark.

Data Engineer

  • Pendahuluan Infrastruktur Big Data & Data Governance.
  • Basis Data relasional tingkat lanjut.
  • NoSQL Documents: MongoDB & ElasticSearch.
  • NoSQL Graph: Neo4J.
  • Pendahuluan Big Data Framework Hadoop & Spark.
  • Network & Database security.
  • High Performance Network and Database.

AI Engineer

  • Pendahuluan Full-Stack programmer.
  • AI solution scalability, availability, and security in Big Data Frameworks.
  • Deep Learning dan Reinforcement Learning tingkat lanjut.
  • Advance data gathering.
  • AI Projects and Entrepreneurship.

Internet of Things

  • Pendahuluan IoT
  • Standards, Architectures and Interoperability
  • Design & Functioning of Wireless IoT Technologies
  • Understanding & Designing Sensor Electronics
  • Designing & Programming of the Web of Things
  • Physical IoT Infrastructure and Network Planning: from Devices to Cloud
  • IoT Data Security, Privacy and Trust
  • IoT Entrepreneurship

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