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TT00CN80-3003
Additional information is shared via ITS that is the main communication channel.
Use of AI in assignments: USE OF AI REPORTED.
AI can be used in the creation of outputs, but student must clearly report its use. Failure to disclose the use of AI will be interpreted as fraud. The use of AI may affect to assessment.
Use of AI in exam: USE OF AI PROHIBITED.
The output must be created without the help of AI. The student should use only their own knowledge, understanding and skills. The use of AI is forbidden for a justified reason and will be interpreted as fraud.
TT00CN71-3005
ITS and Teams.
USE OF ARTIFICIAL INTELLIGENCE REPORTED
Allowed, can be used, must be reported. Artificial intelligence can be used in the creation of outputs, but the student must clearly report its use. Failure to disclose the use of AI will be interpreted as fraud. The use of AI may affect the assessment.
TT00CN68-3005
Qualifications:
Before taking an "Introduction to Data Engineering with Python" course, students typically need a foundational understanding of several key areas. Here are the mandatory and recommended prerequisite courses and topics.
1. Mandatory Prerequisites:
1.1. Programming:
1.1.1. Introduction to Programming: Knowledge of programming fundamentals,
including concepts like variables, loops, conditionals, and functions.
1.1.2. Python Programming: Familiarity with Python, including basic syntax, data
types, control structures, and function and modules
1.1.3. Error Handling
1.1.4. Object-oriented programming (OOP)
1.1.5. Data Manipulation: Skills in using Pandas library including DataFrames and
Series, reading, writing, filtering, and transforming data
1.2. Databases: Knowledge of how databases work, including concepts like tables, keys, normalization, and indexing.
2. Recommended Topics:
2.1. Algorithms and Data Structures: Basic understanding of algorithms and data
structures such as arrays, lists, trees, and graphs, which are crucial for data
processing
2.2. Having the fundamental knowledge of cloud services or passing the Cloud Services
Course in TUAS (Lecturer: Ali Khan)
2.3. Version Control Systems: Basic understanding of tools like Git for version control.
2.4. Basic Algebra and Calculus: Fundamental math skills to handle data transformations
and calculations.
2.5. Statistics: Understanding of basic statistical concepts like mean, median, standard
deviation, and probability distributions.
2.6. Being familiar with VirtualBox and Ubuntu