1. Welcome
2. Your Team
3. Course Overview
4. Course Schedule
5. Projects
6. Tech Requirements
7. Classroom Tools
8. Student Expectations
9. Office Hours
10. Student Feedback

Welcome to the part time Data Science course at General Assembly! We are building a global community of lifelong learners who are excited about using data to solve real world problems.

In this program, we will use Python to explore datasets, build predictive models, and communicate data driven insights. Specifically, you will learn how to:

• Define many of the approaches and considerations that data scientists use to solve real world problems.
• Perform exploratory data analysis with powerful programmatic tools in Python.
• Build and refine basic machine learning models to predict patterns from data sets.
• Communicate data driven insights to peers and stakeholders in order to inform business decisions.

• Statistical Analysis with Python:
• Perform visual and statistical analysis on data using Python and its associated libraries and tools.
• Data-Driven Decision-Making:
• Define and determine the trade-offs involving feature selection, model accuracy, and data quality.
• Machine Learning & Modeling Techniques:
• Explore supervised learning techniques, inlcuding classification, regression, and decision trees.
• Visualizations & Presentations:
• Create visualizations and interactive notebooks to present to industry stakeholders.

The curriculum materials for this course are written in Python 3.6.

Instructor: Dami Lasisi

General Assembly's Data Science part time materials are organized into four units.

Here is the schedule we will be following for our part time data science course:

Class recordings are available here

This course will ask you to complete a series of projects in order to practice and apply the skills covered in-class.

At the end of each Unit, you'll work on short structured projects. These activities will test your understanding of that unit’s most important concepts with in-class practice and instructor support.

For those of you who want to go above and beyond, we’ve also included stretch options, bonus activities, and other opportunities for further reading and practice.

You'll also complete a final project, asking you to apply your skills to a real-world or business problem of your choice.

The capstone is an opportunity for you to demonstrate your new skills and tackle a pressing issue relevant to your life, industry, or organization. You’ll create a hypothesis, analyze internal data, and generate a working model, prototype, solution, or recommendation.

You will get structured guidance and designated time to work throughout the course. Final project deliverables include:

• Proposal: Describe your chosen problem and identify relevant data sets (confirming access, as needed).
• Brief: Share a summary of your initial analysis and your next steps with your instructional team.
• Report: Submit a cleanly formatted Jupyter notebook (or other files) documenting your code and process for technical/peer stakeholders.
• Presentation: Present a summary of your business problem, approach, and recommendation to an audience of non-technical executive stakeholders.

1. Project 1: Python Technical Code Challenges
2. Project 2: Exploratory Data Analysis
3. Project 3: Modeling Practice
4. Project 4: Final Project
   • Part 1: Proposal + Dataset
   • Part 2: Initial EDA Brief
   • Part 3: Technical Report
   • Part 4: Presentation

• Project 1: Monday, September 19, 2022
• Project 2: Monday, October 10, 2022
• Project 3: Monday, October 24, 2022
• Project 4 (Final):
  • Proposal + Dataset: Wednesday, September 21, 2022
  • Initial EDA Brief: Wednesday, October 12, 2022
  • Technical Report: Monday, November 7, 2022
  • Presentation: Monday, November 7, 2022

1. 8GB Ram (at least)
2. 10GB Free Hard Drive Space (after installing Anaconda)

Download and Install Anaconda with Python 3.9.

PC only

• Install Git Bash

• Google Chrome

• Text editor (we recommend Atom)

We'll use Slack for our class communications platform. Slack is a messaging platform where you can chat with your peers and instructors. We will use Slack to share information about the course, discuss lessons, and submit projects. Our Slack homepage is datr-829.

Pro Tip: If you've never used Slack before, check out these resources:

• Intro to Slack
• Slack Basics and Shortcuts
• The Ultimate Slack Cheatsheet

• Be on time for class (students may not miss more than 3 days of class)
• Be present - videos cameras should be on during class
• Submit all assignments
• Complete exit tickets and course surveys
• Ask questions

Every week, your instructional team will hold office hours where you can get in touch to ask questions about anything relating to the course. This is a great opportunity to follow up on questions or ask for more details about any topics covered so far.

• Instructor's Office Hours - by appointment

Throughout the course, you'll be asked to provide feedback about your experience. This feedback is extremely important, as it helps us provide you with a better learning experience.

Access exit ticket here