Last modified: 23 Jul 2024 10:43
In this course we will introduce Python and R for the MSc Data Science. This will include common packages used for data science and we will discuss typical programming constructs used in data science.
| Study Type | Postgraduate | Level | 2 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course provides an introduction to both Python and R, two popular open-source languages in data science.
We will introduce the Python programming language, and the jupyter notebook environment. We will introduce basic programming concepts including algorithms, loops, conditional statements, and functions. We will learn how to use the numpy, matplotlib and panda scientific libraries for data analysis and plotting. In R, we will introduce basic programming concepts, how to build vectors, matrices, factors, as well as how to use data frames and lists.
In summary, this course will provide you with an overview of the most important concepts in these two widely used programming languages and equip you with two important tools to analyse data.
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Written comments. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Remember | Learn main programming commands in R |
| Factual | Remember | Learn main programming commands in Python |
| Procedural | Apply | Understand how to build a code in R to solve a specific problem |
| Procedural | Apply | Understand how to build a code in Python to solve a specific problem |
| Reflection | Create | Write own code in Python to solve a data analysis problem |
| Reflection | Create | Write own code in R to solve a data analysis problem |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Written comments |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Remember | Learn main programming commands in Python |
| Procedural | Apply | Understand how to build a code in Python to solve a specific problem |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Written comments |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Remember | Learn main programming commands in R |
| Procedural | Apply | Understand how to build a code in R to solve a specific problem |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Understand how to build a code in Python to solve a specific problem |
| Procedural | Apply | Understand how to build a code in R to solve a specific problem |
| Reflection | Create | Write own code in Python to solve a data analysis problem |
| Factual | Remember | Learn main programming commands in Python |
| Factual | Remember | Learn main programming commands in R |
| Reflection | Create | Write own code in R to solve a data analysis problem |
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