Data Science Course

General Assembly

Program Description

Data Science Course

General Assembly

Skills & Tools

Use Python to mine datasets and predict patterns.

Production Standard

Build statistical models — regression and classification — that generate usable information from raw data.

The Big Picture

Master the basics of machine learning and harness the power of data to forecast what’s next.

Meet Your Support Team

Our educational excellence is a community effort. When you learn at GA, you can always rely on an in-house team of experts to provide guidance and support, whenever you need it.

Instructors

Learn industry-grade frameworks, tools, vocabulary, and best practices from a teacher whose daily work involves using them expertly.

Teaching Assistants

Taking on new material isn’t always easy. Through office hours and other channels, our TAs are here to provide you with answers, tips, and more.

Course Producers

Our alumni love their Course Producers, who kept them motivated throughout the course. You can reach out to yours for support anytime.

See What You'll Learn

Unit 1: Research Design and Exploratory Data Analysis

  • What is Data Science
    • Describe course syllabus and establish the classroom environment
    • Answer the questions: "What is Data Science? What roles exist in Data Science?"
    • Define the workflow, tools, and approaches data scientists use to analyze data
  • Research Design and Pandas
    • Define a problem and identify appropriate data sets using the data science workflow
    • Walkthrough the data science workflow using a case study in the Pandas library
    • Import, format and clean data using the Pandas Library
  • Statistics Fundamental I
    • Use NumPy and Pandas libraries to analyze datasets using basic summary statistics: mean, median, mode, max, min, quartile, inter-quartile, range, variance, standard deviation, and correlation
    • Create data visualization – scatter plots, scatter matrix, line graph, box blots, and histograms – to discern characteristics and trends in a dataset
    • Identify a normal distribution within a dataset using summary statistics and visualization
  • Statistics Fundamental II
    • Explain the difference between causation vs. correlation
    • Test a hypothesis within a sample case study
    • Validate your findings using statistical analysis (p-values, confidence intervals)
  • Instructor Choice
    • Focus on a topic selected by the instructor/class in order to provide deeper insight into exploratory data analysis

Unit 2: Foundations of Data Modeling

  • Introduction to Regression
    • Define data modeling and linear regression
    • Differentiate between categorical and continuous variables
    • Build a linear regression model using a dataset that meets the linearity assumption using the scikit-learn library
  • Evaluating Model Fit
    • Define regularization, bias, and errors metrics;
    • Evaluate model fit by using loss functions including mean absolute error, mean squared error, root mean squared error
    • Select regression methods based on fit and complexity
  • Introduction to Classification
    • Define a classification model
    • Build a K–Nearest Neighbors using the scikit–learn library
    • Evaluate and tune model by using metrics such as classification accuracy⁄error
  • Introduction to Logistic Regression
    • Build a Logistic regression classification model using the scikit learn library
    • Describe the sigmoid function, odds, and odds ratios and how they relate to logistic regression
    • Evaluate a model using metrics such as classification accuracy⁄error, confusion matrix, ROC⁄AOC curves, and loss functions
  • Communicate Results from Logistic Regression
    • Explain the tradeoff between the precision and recall of a model and articulate the cost of false positives vs. false negatives.
    • Identify the components of a concise, convincing report and how they relate to specific audiences ⁄ stakeholders
    • Describe the difference between visualization for presentations vs. exploratory data analysis
  • Flexible Class Session
    • Focus on a topic selected by the instructor ⁄ class in order to provide deeper insight into data modeling

Unit 3: Data Science in the Real World

  • Decision Trees and Random Forest
    • Describe the difference between classification and regression trees and how to interpret these models
    • Explain and communicate the tradeoffs of decision trees vs regression models
    • Build decision trees and random forests using the scikit-learn library
  • Natural Language Processing
    • Demonstrate how to tokenize natural language text using NLTK
    • Categorize and tag unstructured text data
    • Explain how to build a text classification model using NLTK
  • Dimensionality Reduction
    • Explain how to perform a dimensional reduction using topic models
    • Demonstrate how to refine data using latent dirichlet allocation (LDA)
    • Extract information from a sample text dataset
  • Working with Time Series Data
    • Explain why time series data is different than other data and how to account for it
    • Create rolling means and plot time series data using the Pandas library
    • Perform autocorrelation on time series data
  • Creating Models with Time Series Data
    • Decompose time series data into trend and residual components
    • Validate and cross-validate data from different datasets
    • Use the ARIMA model to forecast and detect trends in time series data
  • The Value of Databases
    • Describe the use cases for different types of databases
    • Explain differences between relational databases and document-based databases
    • Write simple select queries to pull data from a database and use within Pandas
  • Moving Forward with your Data Science Career
    • Specify common models used within different industries
    • Identify the use cases for common models
    • Discuss next steps and additional resources for data science learning
  • Flexible Class Session
    • Focus on a topic selected by the instructor⁄class in order to provide deeper insight into data science in the real world
  • Final Presentations
    • Present final presentation to peers, instructor, and guest panelists who will identify strengths and areas for improvement

Financing Options

Need payment assistance? Our financing options allow you to focus on your goals instead of the barriers that keep you from reaching them.

WeLend

Apply for an interest-free loan up to 18 months, or a fixed fee loan up to 48 months.⁵

⁵Must be a Hong Kong citizen or permanent resident.
Financing options differ in each market and are only available to students accepted into our programs.
Contact a local admissions officer for more info.

This school offers programs in:
  • English


Last updated May 2, 2018
Duration & Price
This course is Campus based
Start Date
Start date
Aug. 2018
Sept. 2018
Duration
Duration
10 weeks
Part time
Price
Price
3,950 USD
Information
Deadline
Locations
Australia - Sydney, New South Wales
Start date : Jan. 2019
Application deadline Request Info
End date Request Info
Australia - Brisbane, Queensland
Start date : Jan. 2019
Application deadline Request Info
End date Request Info
Australia - Melbourne, Victoria
Start date : Jan. 2019
Application deadline Request Info
End date Request Info
Hong Kong - Hong Kong
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
Singapore - Singapore
Start date : Aug. 2018
Application deadline Request Info
End date Request Info
USA - Arlington, Virginia
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Los Angeles, California
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - San Francisco, California
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Denver, Colorado
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Washington, District of Columbia
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Atlanta, Georgia
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Chicago, Illinois
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Irvine, California
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Boston, Massachusetts
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - New York, New York
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
Start date : Feb. 2019
Application deadline Request Info
End date Request Info
Start date : Mar. 2019
Application deadline Request Info
End date Request Info
Start date : Apr. 2019
Application deadline Request Info
End date Request Info
USA - Providence, Rhode Island
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - San Jose, California
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Santa Monica, California
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Austin, Texas
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Dallas, Texas
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - USA Online
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
USA - Washington, District of Columbia
Start date : Sept. 2018
Application deadline Request Info
End date Request Info
United Kingdom - London, England
Start date : Aug. 2018
Application deadline Request Info
End date Request Info
Dates
Aug. 2018
United Kingdom - London, England
Application deadline Request Info
End date Request Info
Singapore - Singapore
Application deadline Request Info
End date Request Info
Sept. 2018
USA - Atlanta, Georgia
Application deadline Request Info
End date Request Info
USA - Austin, Texas
Application deadline Request Info
End date Request Info
USA - Boston, Massachusetts
Application deadline Request Info
End date Request Info
USA - Chicago, Illinois
Application deadline Request Info
End date Request Info
USA - Dallas, Texas
Application deadline Request Info
End date Request Info
USA - Denver, Colorado
Application deadline Request Info
End date Request Info
USA - Los Angeles, California
Application deadline Request Info
End date Request Info
USA - Santa Monica, California
Application deadline Request Info
End date Request Info
USA - Irvine, California
Application deadline Request Info
End date Request Info
USA - New York, New York
Application deadline Request Info
End date Request Info
USA - Providence, Rhode Island
Application deadline Request Info
End date Request Info
USA - San Francisco, California
Application deadline Request Info
End date Request Info
USA - San Jose, California
Application deadline Request Info
End date Request Info
USA - Washington, District of Columbia
Application deadline Request Info
End date Request Info
USA - Washington, District of Columbia
Application deadline Request Info
End date Request Info
USA - Arlington, Virginia
Application deadline Request Info
End date Request Info
Hong Kong - Hong Kong
Application deadline Request Info
End date Request Info
USA - USA Online
Application deadline Request Info
End date Request Info
Jan. 2019
Australia - Brisbane, Queensland
Application deadline Request Info
End date Request Info
Australia - Melbourne, Victoria
Application deadline Request Info
End date Request Info
Australia - Sydney, New South Wales
Application deadline Request Info
End date Request Info
Feb. 2019
USA - New York, New York
Application deadline Request Info
End date Request Info
Mar. 2019
USA - New York, New York
Application deadline Request Info
End date Request Info
Apr. 2019
USA - New York, New York
Application deadline Request Info
End date Request Info