Non-Credit Certificates | Online

Data Science for Business

Curriculum

Data Science Course Structure

  • Understand, prepare, and report on data; clean raw data; use SQL to load and query data.
  • Understand the Python programming language and design and write high-performance code.
  • Use statistical methods to solve complex problems with data and take the first steps toward machine learning. 
  • Turn big data into intelligent, actionable insights through artificial intelligence and machine learning.

Required Data Science Courses

Delve into understanding, managing, reporting, and leveraging data. This first module also covers the history and principles of database systems, how to clean raw data, and how to use SQL to load and query data in databases.

Over eight weeks, our Data Engineering course will provide you with a technical overview of how to understand, leverage, and report data. You will be taught how to source, prepare, and manage historical data. You will also learn about the history and principles of database systems, how to clean raw data, and how to use SQL to load and query data in databases.

You will learn to:

  • Understand databases, data classification, data formats, and data profiles;
  • Apply data privacy and security, data ingestion, data quality and preparation techniques;
  • Identify the principles and best practices of relational databases;
  • Identify the principles and best practices of relational databases;
  • Design a system, known as data warehousing, used for reporting and data analysis.

You will be able to:

  • Build and extract insights from document databases;
  • Create reports and dashboards in Tableau using an analytical datastore;
  • Develop a coherent, concise, and realistic analysis, and apply your knowledge and understanding of creating an automated end-to-end data pipeline;
  • Evaluate the similarities and differences between joins and subqueries in coding and decide which is more suitable based on your use case;
  • Implement data collection techniques, such as web scraping and survey;
  • Populate a graph database and extract insights from graph datasets.

Through a highly technical, project-based approach, you will first be introduced to the principles of Python as a programming language and later have the opportunity to create and run your own projects.

Our eight-week Python for Data Science program introduces core concepts of Python as a programming language. This technical program is project-based and presents you with the opportunity to create and run your own Python projects.

You will learn to:

  • Understand Python language;
  • Perform advanced data analysis and processing;
  • Write production-level Python code;
  • Train and evaluate machine learning models;
  • Design and optimize Python code for performance and speed;
  • Write Python code to efficiently process large data sets;
  • Prepare machine learning models for production use.

You will be able to:

  • Create enduring models to be deployed as an API or used for batch scoring;
  • Design code that runs in parallel using multiprocessing and multithreading functionality;
  • Discuss advanced Python functionalities like classes and functions.

Learn how to code and find meaningful, predictive trends in data. You will be provided with the tools to solve data science problems, taking you further into the world of machine learning. By the end of the course, you will be able to present a start-to-finish assessment using exploratory analysis and dimension reduction as well as linear and classification models.

Statistics for Data Science is a highly practical, eight-week course that will provide you with the foundational tools to solve data science problems and prepare you to take the next steps in the world of machine learning.

You will learn to:

  • Leverage a data set to produce a specified set of results
  • Evaluate results and understand the concept of hypothesis testing
  • Perform a Principal Components Analysis (PCA) to provide meaningful insights on the original data set
  • Learn the intricacies of logistic regression, evaluate its outputs, and comprehend how a link function works
  • Perform multiple pairwise comparisons and analyze models with multiple categorical predictors
  • Build a classification model and interpret results
  • Present a start-to-finish analysis with meaningful insights on a data set using exploratory analysis dimension reduction, linear models, and classification models

You will be able to:

  • Solve data science problems and prepare to take the next steps in the world of machine learning
  • Understand RStudio and its application
  • Gain confidence handling and manipulating data
  • Interpret data and be able to communicate it effectively
  • Earn a certificate of completion from the University of Chicago and become part of the UChicago network

By guiding you through the mathematics and theory of machine learning, you will gain key insights into data investigation, exploration, supervised and unsupervised learning, and the transformation of big data into actionable intelligence.

Our eight-week Artificial Intelligence and Machine Learning course explains the mathematical and theoretical principles that support the function of machine learning in the business landscape. Students will acquire a foundation in data investigation, exploration, as well as supervised and unsupervised learning. They will also learn how to transform big data into informed, actionable insights.

You will learn to:

  • Perform unsupervised and supervised machine learning on large-scale, unstructured/structured datasets;
  • Understand important pattern discovery concepts, methods, and applications;
  • Design classification and regression models for prediction and reasoning;
  • Develop a comprehensive grasp of model interpretation and evaluation.

You will be able to:

  • Understand foundational concepts of predictive analytics and machine learning;
  • Interpret big data-related solutions;
  • Use the scripting programming languages, including Python, to process, visualize, and analyze large data sets and implement machine-learning solutions;
  • Earn a certificate of completion from the University of Chicago and join the UChicago network.

This online program will provide you with the techniques and tools you need to turn insights into compelling narratives. Over eight weeks, you will learn the art of conveying data in a meaningful way to support stakeholder decision-making and drive action.

You will learn to:

  • Translate data into economic value while assessing effective data visualization strategies that link insights to business objectives.
  • Analyze data to determine patterns, key insights, action items, and storytelling potential.
  • Describe the key elements of a successful data story: knowing one’s audience, defining a goal, maintaining engagement, and being explicit about the takeaways.
  • Identify where and how a data story achieves its intended goals and where it can be optimized.
  • Use imaging tools to create data visualizations that align with the needs of the data story.

You will be able to:

  • Identify which business needs can be addressed with data.
  • Distill data into key points using reports, dashboards, stories, and infographics.
  • Anticipate and manage questions from varied audiences.
  • Enhance decision-making by using appropriate cues and indicators for specific audiences.
  • Be awarded a certificate of completion from the University of Chicago and become part of the UChicago network.