| Capaian Pembelajaran Mata Kuliah (CPMK) | - Kemampuan untuk menerapkan hubungan ilmiah dan matematis (prinsip atau hukum) dan masukan yang diperlukan untuk masalah yang diberikan pada simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan menganalisis masalah dan mengidentifikasi peluang untuk menghasilkan pernyataan masalah desain terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan mengidentifikasi batasan untuk menghasilkan persyaratan desain terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan mengidentifikasi dan merumuskan permasalahan teknik terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan menganalisis dan menyelesaikan permasalahan teknik terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan menerapkan penggunaan piranti teknik modern dan mengintegrasikan dalam proyek rekayasa terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan mempersiapkan dan mempresentasikan presentasi teknis secara lisan melalui berbagai media terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan mengumpulkan informasi tentang pengetahuan baru melalui media yang tersedia terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
- Kemampuan memasukkan pengetahuan baru ke dalam pekerjaan teknik terkait simulasi dan pemodelan, reinforcement learning, dan deep learning.
| - Ability to apply scientific and mathematical relationships (principles or laws) and necessary inputs to given problems in simulation and modeling, reinforcement learning, and deep learning.
- Ability to analyze problems and identify opportunities to produce design problem statements related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to identify constraints to generate design requirements related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to identify and formulate engineering problems related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to analyze and solve engineering problems related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to apply the use of modern engineering tools and integrate in engineering projects related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to prepare and present technical presentations orally through various media related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to collect information about new knowledge through available media related to simulation and modeling, reinforcement learning, and deep learning.
- Ability to incorporate new knowledge into engineering work related to simulation and modeling, reinforcement learning, and deep learning.
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