A Guide to ATL DSI
Clone or download
Pull request Compare This branch is 11 commits ahead, 4 commits behind dsi-unit-2:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
resources pushing cheatsheets and resources folder Apr 21, 2017
.gitignore
LICENSE.md
README.md
asking-for-help.md
blogging.md
details.md
git_pull_upstream_process.md

README.md

ATL DSI

Unit Structure

General Assembly's v2.0 Data Science Immersive curriculum is made up of five units.

Unit Title Topics Covered Recommended Length of Time
Unit 1 Data Science Foundations Fundamental Statistics, Databases, Python, & other Data Science Tools. Week 1
Unit 2 Exploratory Data Analysis SQL, Data cleaning, Transformation, & Visualization Weeks 2-3
Unit 3 Classical Statistical Models Regression, Classification, & KNN Weeks 4-6
Unit 4 Machine Learning Models Unsupervised Learning, CARTS, Naive Bayes, ARIMA, & NLP Weeks 7-9
Unit 5 Advanced Topics Bayesian Modeling, Split-Testing, & Deep Learning Weeks 10-12

Unit content libraries may include additional material grouped by topic area. Veteran instructors should feel free to select among these additional materials in order to match the needs of their students.

  • Daily Schedule: The DSI baseline curriculum assumes the following daily schedule:
    • 9-10am: Morning Hour
    • 10am-1pm: Lessons & Labs
    • 1pm-2pm: Lunch break
    • 2pm-5pm: Lessons & Labs

Google Calendar


Lesson + Lab Links

Week 1

Monday

Tuesday

Wednesday