data science

Learn to clean up messy data, uncover patterns and insights, make predictions using machine learning, and clearly communicate your findings.

Data Analyst

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets.

Data Engineering with AWS

In this program, students will master data fundamentals applicable to any industry and learn to make data-driven decisions. From collecting and analyzing data to modeling business scenarios, students will learn Excel, SQL, and Tableau, utilizing data visualization skills to communicate findings.

Business Analytics

Learn programming skills needed to uncover patterns and insights in large data sets, running queries with relational databases and working with Unix shell and Git.

Programming for Data Science with Python

Get hands-on experience running data pipelines, designing experiments, building recommendation systems, and more.

Data Scientist

business

Learn to clearly define business issues, prepare and clean data, and implement a variety of predictive modeling techniques.

CRISP-DM

Random forest models

Model evaluation

Data analysis business context

Classification models

Stepwise regression

Dimensionality reduction

Experiment control

Types of data

Decision trees

Data cleaning

Model interpretation

Forecast visualization

Cluster models

Logistic regression

Ets models

Tableau visualizations

Cluster validation

Interpreting test results

Data extraction

Gradient boosting

Data pre-processing

Alteryx

Arima

Linear regression

Statistical sampling

Differencing of time-series data

Univariate time-series analysis

Model scoring

K-means clustering

A/B testing

Data transformation

Predictive Analytics for Business

This Data Visualization Nanodegree program covers four courses on data visualization and storytelling. Students will learn to select appropriate visualizations, design effective dashboards, and tell data stories that uncover insights and make recommendations. They will use Tableau to build interactive dashboards and create polished presentations with data visualizations. Through a series of projects, students will learn to discover user needs, identify key metrics, prototype, and design dashboards, analyze data to find insights and communicate recommendations effectively.

Data Visualization

Learn the latest skills to process data in real-time by building fluency in modern data engineering tools, such as Apache Spark, Kafka, Spark Streaming, and Kafka Streaming.

Data Streaming

This program will equip any learner who wants to develop in-demand skills in data pre-processing, visualization, and analysis using Power BI as the primary tool.

Data Analysis and Visualization with Microsoft Power BI 

The Data Architect Nanodegree program will be to propel learners to an advanced data professional role as a Data Architect. 

Data Architect

This Programming for Data Science with R Nanodegree program provides an overview of data analysis and programming. In the SQL course, students learn to use SQL to answer complex business problems, including basic commands, joins, and aggregations. In the R course, students learn programming fundamentals and topics such as data types, functions, loops, and conditional statements. They learn to read and manipulate data in R, create basic visualizations, and perform statistical analysis. The version control course teaches students to use Git and GitHub to manage versions of programs and collaborate with others. These courses include practical projects where students use their skills to analyze real data.

Programming for Data Science with R 

Executive Leadership

The Data Science for Business Leaders Executive Program equips learners with strategic, human capital, and technical requirements to deliver enhanced business outcomes and develop an organizational data science strategy that unlocks this potential. The course consists of four lessons that provide a broad introduction to data science and what it can do for a business, articulation of a business's strategic objectives, the human capital component of data science, and creating a data and data architecture strategy. The program also includes a capstone project where students prepare a 100-day data science plan for a company of their choosing.

Data Science for Business Leaders

Learn the basic concepts of data analysis and descriptive statistics. Learn how to manipulate, analyze and visualize data in Excel and Google Sheets. Learn about business metrics across a wide range of business areas (marketing, sales, growth and finance). Finally, learn about forecasting sales and financial metrics.

Growth metrics

Sales metrics

Business KPIs

Forecast modeling in spreadsheets

Quantitative data visualization

Chart types

Inferential statistics

Spreadsheet functions

Categorical data visualization

Pivot tables

Data validation in spreadsheets

Marketing metrics

Basic spreadsheet use

Finance metrics

Professional presentations

Basic descriptive statistics

Data visualization in spreadsheets

Introduction to Data

Learn about the data analysis process, key steps in data wrangling, basic data types, summary statistics, how to design good data visualizations, common types of charts and plots, and how to tell a story with your visuals.

Data fluency

Data Analysis & Visualization Fluency

Data literacy is one of the highest-impact, most in-demand skills. In this lesson, we'll introduce you to the fundamental concepts and terms that you'll need to step into the world of data literacy.

Discovering Data Literacy 

Data analysis and visualization is one of the highest-impact, most in-demand skills. In this lesson, we'll introduce you to the fundamental concepts and terms that you'll need to step into this world.

Discovering Data Analysis and Visualization

Data science is one of the highest-impact, most in-demand skills. In this lesson, we'll introduce you to the fundamental concepts and terms that you'll need to step into the world of data science.

Discovering Data Science

Learn to design data models, build data warehouses, build data lakes and lakehouse architecture, create data pipelines, and work with large datasets on the Azure platform using Azure Synapse Analytics, Azure Databricks, and Azure Data Factory.

Data Engineering with Microsoft Azure

Learn Python programming fundamentals such as data types and structures, variables, loops, and functions.

User input handling

NumPy

Python function definition

Python syntax

List comprehension

Python methods

Built-in Python functions

Variable scope

Pandas

Python ides

Anaconda

Docstrings

Python data structures

Python operators

Control flow

Python best practices

Python exception handling

Python scripting

Iterators

Python data types

Python package management

Introduction to Python 

Learn the data science process, including how to build effective data visualizations, and how to communicate with various stakeholders.

Data science fluency

Introduction to Data Science Fluency

The Privacy Engineer Nanodegree program will prepare you to create technical solutions and implement privacy principles by integrating Privacy-by-Design into product development, data infrastructure, and software release lifecycles. By the end of this program, you will be able to use privacy by design to create solutions that ensure the correct implementation of privacy policies, evaluate privacy compliance risks throughout the data lifecycle, recommend mechanisms to address risks, and execute technical controls that reduce risk and improve data protection.

Privacy Engineer

In this course, you will learn how to design a data governance solution that meets your company’s needs. First, you will learn about the different types of metadata and how to build a Metadata Management System, Enterprise Data Model, and Enterprise Data Catalog. Next, you will learn how to perform data profiling using various techniques including data quality dimensions, how to identify remediation options for data quality issues, and how to measure and monitor data quality using data quality scores, thresholds, dashboards, exceptions, and trend
reports. Finally, you will learn the concepts of Master Data and golden record, different types of Master Data Management Architectures, as well as the golden record creation and master data governance processes. 

Data profiling

Logical erds

Metadata management systems

Conceptual erds

Data governance fluency

Enterprise data models

Metadata management

Data governance business context

Data quality assessment

Master data management

Data Governance

Learn what business intelligence analytics is and how enterprises use it. Learners will be introduced to how enterprises can effectively combine different data types and sources to create a sophisticated data model, and what strategies can be used to ensure data accuracy and consistency.

Business Intelligence Analytics

SQL is one of the most versatile tools available when it comes to extracting insights from stored data.
Learn how to execute core SQL commands to define, select, manipulate, control access, aggregate, and join data and data tables. Understand when and how to use subqueries, several window functions, and partitions to complete complex tasks. Clean data, optimize SQL queries and write select advanced JOINs to enhance analysis performance. Explain which cases you would want to use particular SQL commands and apply the results from queries to address business problems. 


all data science Programs

all data science Programs