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QCL Workshop Resources

Workshop Descriptions

Explore various workshops covering data science, machine learning, and programming. Each workshop provides hands-on experience and valuable learning resources.

QCL latex

Latex

LaTeX: Equation Writing (Level 1)

  • Understand the fundamentals of LaTeX, including its purpose and advantages over traditional word processors.
  • Gain proficiency in using Overleaf to create and compile LaTeX documents.
  • Learn to write mathematical equations and symbols effectively in LaTeX.
  • Explore advanced LaTeX features such as formatting, section referencing, figure inclusion, package integration, and source citation.
  • Apply LaTeX skills to produce professional-quality documents, such as homework assignments, senior theses, or manuscripts.
  • Participants will be able to utilize LaTeX to enhance clarity, consistency, and aesthetics in their academic writing projects.
  • Develop the ability to collaborate and share LaTeX documents online using platforms like Overleaf.
  • Gain confidence in using LaTeX for various academic and professional purposes.
qcl py

Python

Python: Programming Basics Part 1 (Level 1)

  • Set up the Python programming environment using Anaconda and Jupyter Notebook.
  • Understand version control with Git/GitHub.
  • Learn about Python functions and how to create them.
  • Explore variables and their usage in Python.
  • Gain proficiency in essential data structures such as lists and dictionaries.
  • Master the implementation of for loops for iterative tasks.
  • Understand conditional statements (if…else…) and their role in decision making.
  • Engage in a hands-on task to apply learned concepts, potentially involving grocery shopping optimization.

Python: Programming Basics Part 2 (Level 1)

  • Set up Python Programming Environment:
    • Install and utilize Anaconda
    • Use Jupyter Notebook for Python development
    • Understand Version Control System using Git/GitHub
  • Understand Functions in Python.
  • Learn about Variables in Python.
  • Explore Data Structures:
    • Lists
    • Dictionaries
  • Implement For Loops in Python.
  • Master Conditional Statements (if… else…) in Python.

Python: Manipulating Data - Level 2

  • Understand the challenges of working with real-world data and the importance of data cleaning.
  • Familiarize with Pandas and its capabilities for data manipulation and visualization.
  • Learn techniques for extracting data from various sources.
  • Develop skills in transforming data to meet analysis requirements.
  • Gain proficiency in cleaning data to remove inconsistencies and errors.
  • Explore methods for visualizing data to gain insights.
  • Apply Pandas functions and methods to perform common data manipulation tasks.
  • Practice handling missing data and outliers effectively.
  • Enhance Python programming skills within the context of data analysis.
  • Gain confidence in utilizing Jupyter Notebooks for interactive data analysis.
QCL R

R

R: Programming Basics (Level 1)

  • Import and export data efficiently.
  • Filter and transform data using dplyr.
  • Visualize data effectively with ggplot.
  • Apply basic logical operations to manipulate data.

R: Data Exploration (Level 2)

  • Import and export data
  • Clean, reshape, and transform data
  • Convert messy data into tidy data
QCL SQL

SQL

SQL: Setting Up Databases using DBeaver - Part 1

  • Use DBeaver and SQL statements to:
  • Create a database
  • Define table elements
  • Import tables
  • Insert data into your project

SQL: Getting Insights from Databases using DBeaver - Part 2

  • Inserting data
  • Querying a table
  • Joining tables
  • Hands-on activities
qcl git

GIT

GIT: Version Control for Beginners

  • Version Control systems
  • Git and Github
  • Create an organization
  • Create a repository
  • Create issues
  • Forking a repository
  • Cloning a repository
  • Branching a project
  • Contributing to a repository
  • Code review and merging
qcl arcgis

ArcGIS

ArcGIS Online: Exploring GIS Libraries

  • What is GIS?
  • Classic ArcGIS online overview
  • Base and Layers
  • Analysis
  • Edits
  • Save and Send to New ArcGIS Online
  • Print and Share
  • Endnotes
QCL Stata

Stata

STATA Bootcamp (Level 1)

  • Understand the Stata console interface
  • Learn to log results for reproducibility
  • Master techniques for importing and merging data sets
  • Acquire skills in cleaning and preprocessing data
  • Develop proficiency in interactive and batch mode programming
  • Familiarize with common Stata commands and their applications
  • Recognize and avoid common mistakes in Stata programming
  • Learn methods for estimating correlations and descriptive statistics
  • Gain knowledge in graphing data effectively
  • Understand regression analysis techniques in Stata
  • Explore advanced methods such as panel data analysis
  • Learn to implement loops for efficient programming in Stata
QCL Excel

Excel

Excel: Exploring Data - Level 1 Workshop

  • Understand basic features and functions of Microsoft Excel.
  • Learn how to perform data analysis tasks such as sorting, filtering, and applying conditional formatting.
  • Familiarize with a selection of useful keyboard shortcuts for efficiency.
  • Gain proficiency in using VLOOKUP function for data retrieval and analysis.

Excel: Conditioning Data - Level 2 Workshop

  • Understand the functionality and application of Pivot Tables in Excel.
  • Gain proficiency in advanced lookup functions including VLOOKUP (approximate match), INDEX, and MATCH.
  • Learn to utilize common functions such as Count and Sum for data analysis and manipulation.
  • Acquire skills in logical functions including IF, AND, OR, and NOT for decision-making in Excel.
  • Build upon basic Excel skills to enhance efficiency and productivity in spreadsheet tasks.
  • Apply learned concepts to real-world scenarios to improve data management and analysis capabilities.
QCL Tableau

Tableau

Tableau: Visualization (Level 1)

  • Understand the capabilities of Tableau as a powerful and flexible analytics platform.
  • Explore the Tableau Public Gallery to gain insight into data visualization possibilities.
  • Identify the target audience as beginners in data visualization with no prior programming knowledge required.
  • Acquire access to Tableau software through one-year licenses for academic faculty and students or trial versions.
  • Install Tableau Desktop for practical participation in the workshop.
  • Gain familiarity with Tableau Desktop Workspace to navigate the platform effectively.
  • Learn about Tableau Data Connections to import and manage datasets.
  • Practice filtering data to refine insights and focus on relevant information.
  • Master sorting and calculations to manipulate data effectively within Tableau.
  • Create various types of charts and graphs for data visualization purposes.
  • Explore techniques for sharing and exporting insights generated in Tableau.
  • Ensure readiness by confirming the availability of Tableau Desktop on personal computers.

Need Help?

Email: QCL@cmc.edu