Logical Thinking and Programming with Python and Group Project

MQF Level 7

6 Credits (ECTS)

Logical Thinking and Programming with Python and Group Project

Start
October 2024
Module Type
Compulsory
Price
€975
ECTS Credits
6 Credits (ECTS)
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Get 70% back via Tax Credit

€683 refund on this module

Module Description

This module has two parts. The first part of the module will equip learners with the basic understanding of what Python is, its strength and weakness, Python identifiers and variables.

Learners will also learn various components of Python and installation procedure. Learners will also get an exposure of Operator in Python and Functions.

The second part of the module will equip learners with different modules of Python and Python File Handling and Exception Handling.

Learners will also get an exposure of basics of Object-Oriented Programming and Regular Expressions such as Class, Object, Inheritance, Polymorphism, Information hiding and function overloading and overriding etc.

Entry Requirements

Candidates who apply for this course must possess one of the following: 

  • a Level 6 degree related to AI/Computer-Science/Mathematics/Electronics; 

OR 

  • a Level 6 degree not related to AI/Computer Science/Mathematics/Electronics and a minimum of two years’ relevant experience; 

 OR 

  • a Level 5 diploma or higher diploma and five years’ of relevant work experience.   

Target Audience

This course is targeted at: 

  • Industry professionals working in different domains, including Technology, Engineering, Science, IT, Finance, Accountancy, Management, Marketing, Insurance, Banking, Gaming, Healthcare, Medicine, Pharmaceutical, Human Resources, Psychology, Blockchain, Legal, Administration, Policy Making, Digital Art, Archaeology, Architecture, Education and other related areas. 
  • Recent graduates with degrees in Computer Science, Technology, Marketing, Finance, Economics, Accountancy, Management, HR, Law, Engineering, Science, Medicine, Psychology, Digital Art, Game Development, Archaeology, Architecture or Business. 
  • Mid-career-break professionals looking for opportunities to return to or change their career.  

The target group may also be extended to positions such as that of wedding manager, transport manager, maintenance manager, operations manager, marketing manager, conference manager and even that of general manager. 

Module / Unit Instructions

The proposed structure comprises a blended approach promoting the building of a community of practice via peer-to-peer learning.

The structure uses primarily two dimensions of teaching-learning modes:

  1. Face-to-face sessions: 18 hours.
  2. Online Learning Activities: 12 hours.

Face to Face sessions

  • Face-to-face sessions include lectures, tutorials, discussions, presentations and workshop activities promoting peer-to-peer learning.

Online Learning Activities

Online learning activities incorporate tutorials and asynchronous discussions. These may consist of active interaction, participation and contributions in fora discussions, sharing resources and self-reflection exercises.

Learners also contribute to the building of the community of practice by providing feedback to their peers as critical friends, enhancing the learner’s critical engagement throughout the study period.

The tutor provides continual support during both teaching -learning modes by providing information, readings and tasks relevant to the module in question.

The tutor provides continuous formative feedback as an on-going guidance during the student’s learning experience in preparation for their summative assessment.

How you’ll be assessed

Assessment of each module consists of two assignments, each carrying a weighting as below:

a) One Formative assignment carries 20% of total module mark achieved. b) One Summative assignment carries 80% of total module mark achieved.

For successful completion of a study module the student is required to achieve a minimum of 41% pass mark in both the formative and the summative assignment.

The overall grade achieved for each module is calculated as the sum of:  20% of the mark achieved for formative assignment; and  80% of the mark achieved for the summative assignment.

All assignment tasks of both formative and summative assessment aim to provide the learner an opportunity to produce evidence of his/her competences aligned to the learning outcomes of each individual Module.

Assessment

a) Formative assessment tasks are provided in the form of structured online discussions that support learners in their development throughout all of the modules studied.

Such discussions are facilitated and monitored by lecturer who provides students with constructive feedback to help them improve and prepare for summative assignment and dissertation.

Formative assessment tasks will contribute to the student’s final mark to acknowledge their work and give chance to improve.

This method allows students to also contribute to the building of the community of practice by providing feedback to their peers as critical friends, enhancing the learner’s critical engagement throughout the study period.

b) Summative assessment is done via one assignment at the end of each module.

The mode of assessment varies and may include in-class assignments, and home-based written assignments.

For module 3 the recommended assessment tool is programming projects or drawing proposals. Other assessment tools which may be used are case studies.

Word count range: 3000 ± 10% For successful completion of a study module, the student is required to achieve a minimum of 41% pass mark in the summative assignment.

 

Assignment
Discussions

Module Intake Dates

October 2024
Price
€975

Additional Info

Reading for the entire Master of Science (M.Sc.) in Artificial Intelligence as presented in this brochure costs €9,775.*  

Upon successful completion of this course, students will be eligible for a 70% refund of the cost through the ‘Get Qualified’ scheme.** 

Due to the modular structure of the course, you may also opt to take individual modules as stand-alone. The entry requirements still apply.***  

*Prices are applicable to students who reside in Malta at the time of applying. 

**Terms and conditions apply.  

*** For the price of individual modules, please contact the IDEA Academy team.  

Learning Outcomes

Knowledge: – at the end of the module/unit the learner will have been exposed to the following:

  • Examine the History of Python, its Strength and Weakness and Different Versions.
  • Discuss Python functions, modules and file handling implications.
  • Categorise elements of object-oriented programming and regular expression.
  • Examine the Exception Model and its hierarchy.

Key indicative topic areas cover:

  • Introduction to Python
  • Python Syntax
  • Python Collections or Sequence
  • Python Functions
  • Python module
  • Python File Handling
  • Object-Oriented programming
  • Regular Expression
  • Exception Handling

Skills:

At the end of the module/unit the learner will have acquired the following skills:

  • Install different versions of Python.
  • Appropriately apply Variables in Python, Data types, Operator and loop statements including break and continue etc.
  • Judiciously use different Python functions · thoroughly understand Python modules and Dir() functions.
  • Properly apply essential Python file handling functions and different file working attributes.
  • Develop a Python program to effectively implement an algorithm and perform a programming task.

Judgment Skills and Critical Abilities:

The learner will be able to:

  • Collect, analyse and interpret data/information to support arguments, and to develop and apply ideas.

Module-Specific Communication Skills:

The learner will be able to:

  • Communicates ideas, problems, and solutions to both specialist and non-specialist audiences using a range of techniques involving qualitative and quantitative information to sustain arguments.

Module-Specific Learner Skills:

  • Undertake independent and self-directed study through primary and secondary research.

Module-Specific Digital Skills and Competences:

The learner will be able to:

  • Navigate through the online learning platform to find assignments, discussion boards, literature, tutorials etc.
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