Digital Skills Lab workshop booking links

The booking links below are for in-person workshops. All in person workshops will take place on campus in LRB.R.08 in the lower ground floor of the Library. To keep our teaching staff safe we are asking learners to wear masks during the training session. If you are not comfortable with this we request that you attend an online workshop instead. The content for the online and in-person workshops are the same. 

Click on the topic below to book your next workshop or express your interest so you're notified as soon as a new workshop is scheduled.

Excel and VBA

• Excel 1: Calculated Worksheets
• Excel 2: Numeric Calculations
• Excel 3: Essential Functions
• Excel 4a: Lookup Functions
• Excel 4b: Pivot Tables
• Excel 4c: Sorting and Filtering
• Excel 4d: Charting Data
• Excel 4e: Data Tools
• Excel 4f: What-if Analysis
• Excel 5: Complex Calculations
• Excel 6: Using Macros

• VBA 1: Elements and Variables
• VBA 2: Worksheet Manipulation
• VBA 3: Data Manipulation
• VBA 4: Debugging and Troubleshooting
• VBA 5: Report Generation

PowerPoint

• PowerPoint 1: Designing Slides
• PowerPoint 2: Formatting Slides
• PowerPoint 3: Professional Slides

Python

• Python Fundamentals 1: Numerical Variables
• Python Fundamentals 2: String Variables
• Python Fundamentals 3: Converting
• Python Fundamentals 4: Lists
• Python Fundamentals 5: List of lists
• Python Fundamentals 6: Functions
• Python Fundamentals 7: For loops
• Python Fundamentals 8: Conditionals
• Python Fundamentals 9: Writing functions

• Working with Tabular Data 1: NumPy Arrays
• Working with Tabular Data 2: NumPy 2D Arrays
• Working with Tabular Data 3: Pandas Basics
• Working with Tabular Data 4: Pandas Indexing
• Working with Tabular Data 5: Pandas Data Exploring

• Data Visualization in Python 1: Line Plots with Matplotlib
• Data Visualization in Python 2: Scatter, Bar Plots and Histograms with Matplotlib
• Data Visualization in Python 3: Plotting with Pandas and Seaborn

R

• R Fundamentals 1: Numerical Variables
• R Fundamentals 2: Vectors, Functions, and Indexing
• R Fundamentals 3: Strings, Factors, and Type Conversion
• R Fundamentals 4: Data Frames
• R Fundamentals 5: Loading data and packages
• R Fundamentals 6: Conditionals and Logic
• R Fundamentals 7: Lists and Matrices

• R Data Wrangling 1: Pipes and introduction to dplyr
• R Data Wrangling 2: Data wrangling with dplyr continued
• R Data Wrangling 3: Joining and aggregation

• R Data Visualisation 1: Data viz with ggplot2
• R Data Visualisation 2: Box, histogram and line plots

SPSS

• SPSS 1: Foundations of Data Management
• SPSS 2: Data Exploration
• SPSS 3: Introduction to inferential statistics
• SPSS 4: Regressions in SPSS

Stata

• Stata Fundamentals 1: Import and inspecting data
• Stata Fundamentals 2: Do-files and computing variables
• Stata Fundamentals 3: Linear regression
• Stata Fundamentals 4: Foreach Loops
• Stata Fundamentals 5: if qualifiers

• Data Cleaning in Stata 1: Strings
• Data Cleaning in Stata 2: Missing values
• Data Cleaning in Stata 3: Labels
• Data Cleaning in Stata 4: Reshaping data
• Data Cleaning in Stata 5: Merging data

Tableau

• Tableau 1: Introduction to Tableau
• Tableau 2: Filtering and Sorting
• Tableau 3: Geographic Data and Relationships
• Tableau 4: Time Series and Aggregations

Word

•  Word 1: Dissertation Timesavers and Troubleshooting

The booking links below are for online workshops. Our productivity workshops (Excel/VBA, PowerPoint and Word) take place via Teams and all other workshops take place via Zoom.  Please make sure you meet the technical requirements for your chosen online workshop listed below, otherwise we recommend you attend an in-person workshop instead. The content for the online and in-person workshops are the same. 

Click on the topic below to book your next workshop or express your interest so you're notified as soon as a new workshop is scheduled.

Excel and VBA

Technical requirements for online Excel and VBA workshops

• Excel 1: Calculated Worksheets (online)
• Excel 2: Numeric Calculations (online)
• Excel 3: Essential Functions (online)
• Excel 4a: Lookup Functions (online)
• Excel 4b: Pivot Tables (online)
• Excel 4c: Sorting and Filtering (online)
• Excel 4d: Charting Data (online)
• Excel 4e: Data Tools (online)
• Excel 4f: What-if Analysis (online)
• Excel 5: Complex Calculations (online)
• Excel 6: Using Macros (online)

• VBA 1: Elements and Variables (online)
• VBA 2: Worksheet Manipulation (online)
• VBA 3: Data Manipulation (online)
• VBA 4: Debugging and Troubleshooting (online)
• VBA 5: Report Generation (online)

PowerPoint

Technical requirements for online PowerPoint workshops

• PowerPoint 1: Designing Slides (online)
• PowerPoint 2: Formatting Slides (online)
• PowerPoint 3: Professional Slides (online)

Python 

Technical requirements for online Python workshops

• Python Fundamentals 1: Numerical Variables (online)
• Python Fundamentals 2: String Variables (online)
• Python Fundamentals 3: Converting (online)
• Python Fundamentals 4: Lists (online)
• Python Fundamentals 5: List of lists (online)
• Python Fundamentals 6: Functions (online)
• Python Fundamentals 7: For loops (online)
• Python Fundamentals 8: Conditionals (online)
• Python Fundamentals 9: Writing functions (online)

• Working with Tabular Data 1: NumPy Arrays (online)
• Working with Tabular Data 2: NumPy 2D Arrays (online)
• Working with Tabular Data 3: Pandas Basics (online)
• Working with Tabular Data 4: Pandas Indexing (online)
• Working with Tabular Data 5: Pandas Data Exploring (online)

• Data Visualization in Python 1: Line Plots with Matplotlib (online)
• Data Visualization in Python 2: Scatter, Bar Plots and Histograms with Matplotlib (online)
• Data Visualization in Python 3: Plotting with Pandas and Seaborn (online)

R

Technical requirements for online R workshops

• R Fundamentals 1: Numerical Variables (online)
• R Fundamentals 2: Vectors, Functions, and Indexing (online)
• R Fundamentals 3: Strings, Factors, and Type Conversion (online)
• R Fundamentals 4: Data Frames (online)
• R Fundamentals 5: Loading data and packages (online)
• R Fundamentals 6: Conditionals and Logic (online)
• R Fundamentals 7: Lists and Matrices (online)

• R Data Wrangling 1: Pipes and introduction to dplyr (online)
• R Data Wrangling 2: Data wrangling with dplyr continued (online)
• R Data Wrangling 3: Joining and aggregation (online)

• R Data Visualisation 1: Data viz with ggplot2 (online)
• R Data Visualisation 2: Box, histogram and line plots (online)

SPSS

Technical requirements for online SPSS workshops

• SPSS 1: Foundations of Data Management (online)
• SPSS 2: Data Exploration (online) 
• SPSS 3: Introduction to inferential statistics (online)
• SPSS 4: Regressions in SPSS (online)

Stata

Technical requirements for online Stata workshops

• Stata Fundamentals 1: Import and inspecting data (online)
• Stata Fundamentals 2: Do-files and computing variables (online)
• Stata Fundamentals 3: Linear regression (online)
• Stata Fundamentals 4: Foreach Loops (online)
• Stata Fundamentals 5: if qualifiers (online)

• Data Cleaning in Stata 1: Strings (online)
• Data Cleaning in Stata 2: Missing values (online)
• Data Cleaning in Stata 3: Labels (online)
• Data Cleaning in Stata 4: Reshaping data (online)
• Data Cleaning in Stata 5: Merging data (online)

Tableau

Technical requirements for online Tableau workshops

• Tableau 1: Introduction to Tableau (online)
• Tableau 2: Filtering and Sorting (online)
• Tableau 3: Geographic Data and Relationships (online)
• Tableau 4: Time Series and Aggregations (online)

Word

Technical requirements for online Word workshops

• Word 1: Dissertation Timesavers and Troubleshooting (online)

Excel 1: Calculated Worksheets (online)

Excel 1: Calculated Worksheets

Excel 2: Numeric Calculations (online)

Excel 2: Numeric Calculations

Excel 3: Essential Functions (online)

Excel 3: Essential Functions

Excel 4a: Lookup Functions (online)

Excel 4a: Lookup Functions

Excel 4b: Pivot Tables (online)

Excel 4b: Pivot Tables

Excel 4c: Sorting and Filtering (online)

Excel 4c: Sorting and Filtering

Excel 4d: Charting Data (online)

Excel 4d: Charting Data

Excel 4e: Data Tools (online)

Excel 4e: Data Tools

Excel 4f: What-if Analysis (online)

Excel 4f: What-if Analysis

Excel 5: Complex Calculations (online)

Excel 5: Complex Calculations

Excel 6: Using Macros (online)

Excel 6: Using Macros

VBA 1: Elements and Variables (online)

VBA 1: Elements and Variables

VBA 2: Worksheet Manipulation (online)

VBA 2: Worksheet Manipulation

VBA 3: Data Manipulation (online)

VBA 3: Data Manipulation

VBA 4: Debugging and Troubleshooting (online)

VBA 4: Debugging and Troubleshooting

VBA 5: Report Generation (online)

VBA 5: Report Generation

PowerPoint 1: Designing Slides (online)

PowerPoint 1: Designing Slides

PowerPoint 2: Formatting Slides (online)

PowerPoint 2: Formatting Slides

PowerPoint 3: Professional Slides (online)

PowerPoint 3: Professional Slides

Python Fundamentals 1: Numerical Variables (online)

Python Fundamentals 1: Numerical Variables

Python Fundamentals 2: String Variables (online)

Python Fundamentals 2: String Variables

Python Fundamentals 3: Converting (online)

Python Fundamentals 3: Converting

Python Fundamentals 4: Lists (online)

Python Fundamentals 4: Lists

Python Fundamentals 5: List of lists (online)

Python Fundamentals 5: List of lists

Python Fundamentals 6: Functions (online)

Python Fundamentals 6: Functions

Python Fundamentals 7: For loops (online)

Python Fundamentals 7: For loops

Python Fundamentals 8: Conditionals (online)

Python Fundamentals 8: Conditionals

Python Fundamentals 9: Writing functions (online)

Python Fundamentals 9: Writing functions

Working with Tabular Data 1: NumPy Arrays (online)

Working with Tabular Data 1: NumPy Arrays

Working with Tabular Data 2: NumPy 2D Arrays (online)

Working with Tabular Data 2: NumPy 2D Arrays

Working with Tabular Data 3: Pandas Basics (online)

Working with Tabular Data 3: Pandas Basics

Working with Tabular Data 4: Pandas Indexing (online)

Working with Tabular Data 4: Pandas Indexing

Working with Tabular Data 5: Pandas Data Exploring (online)  

Working with Tabular Data 5: Pandas Data Exploring

Data Visualization in Python 1: Line Plots with Matplotlib (online)

Data Visualization in Python 1: Line Plots with Matplotlib

Data Visualization in Python 2: Scatter, Bar Plots and Histograms with Matplotlib (online)

Data Visualization in Python 2: Scatter, Bar Plots and Histograms with Matplotlib

Data Visualization in Python 3: Plotting with Pandas and Seaborn (online)

Data Visualization in Python 3: Plotting with Pandas and Seaborn

R Fundamentals 1: Numerical Variables (online)

R Fundamentals 1: Numerical Variables

R Fundamentals 2: Vectors, Functions, and Indexing (online)

R Fundamentals 2: Vectors, Functions, and Indexing

R Fundamentals 3: Strings, Factors, and Type Conversion (online)

R Fundamentals 3: Strings, Factors, and Type Conversion

R Fundamentals 4: Data Frames (online)

R Fundamentals 4: Data Frames

R Fundamentals 5: Loading data and packages (online)

R Fundamentals 5: Loading data and packages

R Fundamentals 6: Conditionals and Logic (online)

R Fundamentals 6: Conditionals and Logic

R Fundamentals 7: Lists and Matrices (online)

R Fundamentals 7: Lists and Matrices

R Data Wrangling 1: Pipes and introduction to dplyr (online)

R Data Wrangling 1: Pipes and introduction to dplyr

R Data Wrangling 2: Data wrangling with dplyr continued

R Data Wrangling 2: Data wrangling with dplyr continued (online)

R Data Wrangling 3: Joining and aggregation (online)

R Data Wrangling 3: Joining and aggregation

R Data Visualisation 1: Data viz with ggplot2 (online)

R Data Visualisation 1: Data viz with ggplot2

R Data Visualisation 2: Box, histogram and line plots (online)

R Data Visualisation 2: Box, histogram and line plots

SPSS 1: Foundations of Data Management (online)

SPSS 1: Foundations of Data Management

SPSS 2: Data Exploration (online) 

SPSS 2: Data Exploration

SPSS 3: Introduction to inferential statistics (online)

SPSS 3: Introduction to inferential statistics

SPSS 4: Regressions in SPSS (online)

SPSS 4: Regressions in SPSS

Stata Fundamentals 1: Import and inspecting data (online)

Stata Fundamentals 1: Import and inspecting data

Stata Fundamentals 2: Do-files and computing variables (online)

Stata Fundamentals 2: Do-files and computing variables

Stata Fundamentals 3: Linear regression (online)

Stata Fundamentals 3: Linear regression

Stata Fundamentals 4: Foreach Loops (online)

Stata Fundamentals 4: Foreach Loops

Stata Fundamentals 5: if qualifiers (online)

Stata Fundamentals 5: if qualifiers

Data Cleaning in Stata 1: Strings (online)

Data Cleaning in Stata 1: Strings

Data Cleaning in Stata 2: Missing values (online)

Data Cleaning in Stata 2: Missing values

Data Cleaning in Stata 3: Labels (online)

Data Cleaning in Stata 3: Labels

Data Cleaning in Stata 4: Reshaping data (online)

Data Cleaning in Stata 4: Reshaping data

Data Cleaning in Stata 5: Merging data (online)

Data Cleaning in Stata 5: Merging data

Tableau 1: Introduction to Tableau (online)

Tableau 1: Introduction to Tableau

Tableau 2: Filtering and Sorting (online)

Tableau 2: Filtering and Sorting

Tableau 3: Geographic Data and Relationships (online)

Tableau 3: Geographic Data and Relationships

Tableau 4: Time Series and Aggregations (online)

Tableau 4: Time Series and Aggregations

Word 1: Dissertation Timesavers and Troubleshooting (online)

Word 1: Dissertation Timesavers and Troubleshooting