Our Data paths are growing in popularity, from students who just want to improve their data skills in an existing job to career transitions to a professional role as a Data Analyst. Here are some wonderful resources to help you in our Data-based bootcamp, boost, or pivot paths!
Boost: Database Querying with SQL
Pre-Apprenticeship and Bootcamp Projects
- Project 1: "Explore a Dataset on Energy Usage and Draw your First Conclusions"
Skills:Create a spreadsheet and a slidedeck presentation - Project 2 "Create a Dashboard Meeting Business Requirements" - Webinar Link
Skills: distribution (e.g. histogram or boxplot), composition (e.g. pie chart), comparison (e.g. bar chart), trend over time (e.g. time series), and relationship (e.g. scatter plot) - Project 3 "Assess the Quality of a Dataset for a Public Service Agency"
Skills: Jupyter notebook, principles of data, and data classification - Project 4 "Retrieve User Activity Data on an Online Forum using SQL"
Skills: SQL, data structures, database design, Jupyter notebook
Apprenticeship Projects
- Project 1: "Dive Into your Data Analyst Apprenticeship"
- Project 2: "Analyze Requirements and Plan a Data Analysis"
- Project 3: "Perform Initial Data Analysis and Modeling Based on Sales Data"
- Project 4: "Analyze an Existing Database and Retrieve Data"
- Project 5: "Prepare Data for analysis and Assess its Quality "
- Project 6: "Produce a Dashboard to Visualize Data"
- Project 7: "Keep Track of Emerging Data Analysis Industry and technology Trends"
Click here to view "How to do Project 7 in an afternoon"
Webinars
- 📺 Data Confidence, or how to interpret data - Link
- 📺 SQL & Data Workshop - Link
- 📺 Data Demo: Jupyter Notebooks - Link
- 📺 Using Data and SQL for Social Media projects - Link
- 📺 Statistics Refresher Hour - Link
Pivot: Data Analyst
- Project 1: "Start your journey as a Data Analyst"
Skills: An introductory project to welcome you to the program and familiarize yourself with the OpenClassrooms platform - Project 2: "24 hours in the life of a Data Analyst"
Skills: A practical, short project about your future career. Try to finish this quickly! - Project 3: "Improve your client's Social Media strategy"
Skills: SQL, Relational Algebra, Relational Model in Datasets - Project 4: "Conduct a public health study"
Skills: Using Python, Relational Algebra, Jupyter Notebook - Project 5: "Analyze your company’s sales"
Skills: bivariate and univariate analysis - Project 6: "Conduct a market analysis"
Skills: hierarchical clustering and statistical testing - Project 7: "Detect counterfeit notes"
Skills: Modeling techniques, k-means algorithm, principal component analysis - Project 8: "Make an income prediction"
Skills: linear regression and analysis of variance (ANOVA) - Project 9: "Help your company visualize their progress"
Skills: presenting data as a dashboard
- 📺 SQL & Data Workshop - Link
An interactive workshop to learn how to use SQL Querying - 📺 Data Demo: Jupyter Notebooks - Link
Jupyter Notebooks are a critical tool for complex data management. Watch as we set one up together! - 📺 Using Data and SQL for Social Media projects - Link
Our mentor demonstrates how data helps in all areas of the digital world, including social media. - 📺 Database Querying with SQL Boost - Link
An Introduction to this 2 month Boost path and how to do its one project - 📺 Database Querying with SQL: How to finish the project - Link
An assessor goes over SQLite and filters before offering advice on how to prepare for the defense - 📺 Data Confidence, or how to interpret data - Link
General advice for students of all paths using data of any kind but especially digital data students
Statistics Refresher Resources
- The Organic Chemistry Tour's Introduction to Statistics - Link
- Zedstatistics "Teach me Statistics in Half and Hour!" - Link
- Pearson's Correlation Coefficient - Link
- Professor Dave Explains Linear Algebra: Systems of Linear Equations - Link
- Andrew Thangaraj Linear Algebra - Link
- ACAGILD Probability and Statistics - Link
- Definitions and tutorials for Basic Probability - Link
- The Basics of Mathematical Modeling - Link
- Numerical Analysis: Tips and Tricks for the Bisection Method - Link
- Numerical Methods Using Python - Link
