Structure
In Specialization 1 - Bootcamp and Binary Classification you learn the basics of data science, ranging from useful pandas functions to procedures like data cleaning and common problems like regression and classification and the models used to tackle them. This first Specialization has a different structure than other Specializations. It is composed of 3 learning units completed during the admissions and additional 14 mandatory and 2 optional learning units which you have to complete in the first three weeks of the Academy`. The learning units are accompanied by virtual classes presented during 2 days. Participation in the virtual classes is mandatory.
| SLU | Name | Presented at | Mandatory |
|---|---|---|---|
| SLU01 | Pandas 101 | Admissions | Yes |
| SLU02 | Subsetting Data in Pandas | Admissions | Yes |
| SLU03 | Visualization with Pandas & Matplotlib | Admissions | Yes |
| SLU04 | Basic Stats with Pandas | Bootcamp Day 1 | Yes |
| SLU05 | Covariance & Correlation | Bootcamp Day 1 | Yes |
| SLU06 | Dealing with Data Problems | Bootcamp Day 1 | Yes |
| SLU07 | Regression with Linear Regression | Bootcamp Day 1 | Yes |
| SLU08 | Metrics for Regression | Bootcamp Day 1 | Yes |
| SLU09 | Classification with Logistic Regression | Bootcamp Day 1 | Yes |
| SLU10 | Metrics for Classification | Bootcamp Day 1 | Yes |
| SLU11 | Tree-Based Models | Bootcamp Day 2 | Yes |
| SLU12 | Feature Engineering (aka Real Wold Data) | Bootcamp Day 2 | Yes |
| SLU13 | Bias-Variance tradeoff & Model Selection | Bootcamp Day 2 | Yes |
| SLU14 | Model complexity & Overfitting | Bootcamp Day 2 | Yes |
| SLU15 | Hyperparameter Tuning | Bootcamp Day 2 | Yes |
| SLU16 | Workflow | Bootcamp Day 2 | Yes |
| SLU17 | Ethics & Fairness | Bootcamp Day 2 | Yes |
| SLU18 | Support Vector Machines (SVM) | Not presented | No |
| SLU19 | k-Nearest Neighbors (kNN) | Not presented | No |
The virtual classes will be presented on Sundays 26 Nov 2023 and 3 Dec 2023. Each class lasts about 60 min. The topics presented during each class are the following:
Bootcamp part 1, Sunday morning 26 Nov 2023
- Class 1:
- Introduction to data science
- SLU04 - Basic Stats with Pandas
- SLU05 - Covariance and Correlation
- SLU06 - Dealing with Data Problems
- Class 2:
- SLU07 - Regression with Linear Regression
- SLU08 - Metrics for Regression
- Class 3:
- SLU09 - Classification with Logistic Regression
- SLU10 - Metrics for Classification
Bootcamp part 2, Sunday morning 3 Dec 2023
- Class 4:
- SLU11 - Tree-Based Models
- SLU12 - Feature Engineering Class 5:
- SLU13 - Bias-Variance tradeoff & Model Selection
- SLU14 - Model complexity and Overfitting
- SLU15 - Hyperparameter Tuning Class 6:
- SLU16 - Workflow
- SLU17 - Ethics and Fairness
Time commitment
Aside from the virtual classes, you should be prepared to spend a recommended 10 hours per week on the bootcamp units throughout the course of the 3 weeks given to complete them.
Specialization 1 Evaluation Rules
In order to pass Specialization 1
- The student must take part in the virtual classes
- The student must score at least 16/20 on the mandatory learning units until the deadline (see the calendar section below)
Optional units
There are a two optional units teaching additional classification models that we recommend the students look at, but that are not mandatory to pass the bootcamp. However, they will show up on the final curriculum as either passed/failed. As in other learning units, a passing grade is a score of at least 16/20 submitted until the deadline. (see the calendar section below). We advise you to only tackle these two units after you have completed all mandatory content, since completing Specialization 1 is essential to proceed with the academy.
Calendar
| Description | Date |
|---|---|
| Bootcamp day 1 | 26 Nov 2023 in the morning |
| Bootcamp day 2 | 3 Dec 2023 in the morning |
| Deadline for Specialization 1 | 16 Dec 2023, 8pm UTC |