Staff Member #1
Biography of instructor/staff member #1
Advanced Programming in Python
CNEAD
About This Course
This document is a comprehensive syllabus for a university course focused on applied computing and data science. The course aims to develop skills in Python programming, data automation, visualization, and introductory AI. Key objectives include mastering Python libraries such as Pandas, NumPy, and Scikit-learn, automating tasks with Excel, and managing projects using GanttProject. The syllabus is structured into six chapters covering Python basics, automation, advanced Excel, project management, object-oriented programming, and data preparation for AI.
It includes practical work sessions and a final project involving data analysis and a simple predictive model. Students are expected to use tools like TensorFlow and PyTorch for machine learning exercises. The course requires prior Python programming knowledge and access to a computer with necessary software installed. Assessment consists of a 60% final exam and 40% continuous evaluation.
Requirements
The objectives of studying "Advanced Programming in Python" can be summarized as follows: To deepen the mastery of the Python language and introduce students to the fundamentals of data analysis and artificial intelligence.
- To acquire a solid foundation in computer science.
- To develop practical programming skills in both Python and Excel.
- To master task automation for improved efficiency.
- To master a project management software.
Course Staff
Staff Member #2
Biography of instructor/staff member #2
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