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Overview

The module enables students to develop coding skills that are highly sought-after by employers. The fundamental concepts that are covered include expression, variables, data structures, control structures, functions. Two widely popular programming languages for data science, R and Python will be used for developing and applying programming skills. On completion of the module, students are well prepared to add value in many business settings and in other organisations.

Topics may include Introduction to R, Data structures in R, Conditional statements in R, Loops and apply functions in R, Functions in R, New packages in R, Introduction to Python, Data manipulation and analysis in Python, Visualisation in Python, Advanced Programming Concepts in Python.

Assessment Strategy

Threshold c- to c+ (50-59%): Satisfactory performance. No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives. Knowledge of key areas/principles only. Weaknesses in understanding of some areas. Limited evidence of background study. Answer inadequately focused on task and with some irrelevant material and poor structure. Arguments presented but lack coherence. Minor factual/computational errors. Lacking original interpretation.

Good B- to B+ (60-69%): Good performance. Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills. Understands most but not all concepts/issues. Evidence of background study. Focused answer with good structure. Arguments presented coherently. Mostly free of factual errors. Some limited original interpretation. Well known links between topics are described. Problems addressed by existing methods/approaches. Good presentation with accurate communication

Excellent standard: 70+ An outstanding performance, exceptionally able. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills.

Learning Outcomes

• Explain and implement key terminologies, concepts and techniques employed in Statistical Analysis.

• Explain and implement methods for visualisation of data.

• Generate programming code in Python and programmatically process files ,

• Implement code for reading from and writing to Excel and CSV files.

• Install, generate code, execute and recognize R Programming Language in R Studio IDE to perform basic tasks on Vectors, Matrices and Data frames.