Data Engineering is the foundation for the new world of Big Data. Enroll now to build production-ready data infrastructure, an essential skill for advancing your data career.
Data Modeling, Data Pipelines, Data Lakes, Spark, Airflow
Intermediate Python & SQL
Insight
Learn the fundamental programming tools for data professionals: Python, SQL, the Terminal and Git.
Python, Numpy & Pandas, SQL, Git & GitHub
None
Mode
Build effective machine learning models, run data pipelines, build recommendation systems, and deploy solutions to the cloud with industry-aligned projects.
Machine Learning, Deep Learning, Software Engineering
Python, SQL & Statistics
Bertelsmann, Figure Eight, IBM Watson, Insight, Kaggle, Starbucks
Gain foundational data skills applicable to any industry. Collect and analyze data, model business scenarios, and communicate your findings with SQL, Excel, and Tableau.
Excel & Spreadsheets, SQL, Data Visualization, Data Dashboards
None
Tableau, Mode
Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions.
Data Wrangling, Matplotlib, Bootstrapping, Pandas & NumPy, Statistics
Python & SQL
Kaggle
Master SQL, the core language for Big Data analysis, and enable insight-driven decision-making and strategy for your business.
SQL, PostgreSQL, JOINs, Subqueries, Window Functions, Partitions, Data Cleaning, DDL, DML, Relational and Non-Relational Databases
Basic understanding of data types
Hone specialized skills in Data Product Management by learning how to apply data science best practices to build data-driven products backed by scalable data strategies to deliver the right experience to the right users, at the right time.
Data Science, Product Management, Product Design, Data Visualization, User Journey Maps
Prior Data Analysis & Product Management Experience Recommended
Learn how to stream data to unlock key insights in real-time.
Data Streaming, Spark, Kafka, Kafka Streaming, Spark Streaming
Intermediate Python, SQL, and experience with ETL
Predictive analytics is the practice of determining patterns from data to predict future outcomes and trends. Across industries, it enables high-value solutions to important business problems.
Data Wrangling, Classification, A/B Testing, Forecasting, Segmentation
Algebra, Descriptive Statistics, and Excel
Alteryx, Tableau
Monetization Strategy is the third of three courses in the Growth Product Manager Nanodegree program. Hone specialized Product Management skills in monetization strategy by learning how to implement strategies to drive profitable growth for your business. Build and test pricing plans and market selection, target the right buyer personas, and be equipped to harness their full lifetime value.
Product Management, Monetization Models, Pricing Strategy, Buyer Personas, Lifetime Value, Customer Acquisition Cost, Pricing Metrics, Growth Strategy
Prior Product Management Experience Recommended
Master the people, platforms, and processes required to leverage the power of Data Science in your business.
Business Strategy, Data Science, Data Architecture, Machine Learning, Human Capital
Statistics, Probability, and Business Experience
Alteryx
Combine data, visuals, and narrative to tell impactful stories and make data-driven decisions.
Data Visualization, Tableau, Dashboards, Data Storytelling
Basic Data Analysis
Prepare for a data science career by learning the fundamental data programming tools: R, SQL, command line, and git.
R, SQL, Git
None
Mode
You’ll master the in-demand skills necessary to become a successful data analyst like data pre-processing, visualization and analysis using Power BI as the primary tool.
Power BI, data visulations, data modeling, Extract-Transform-Load, Data Analytics Expressions
Microsoft Excel
Learn how to plan, design and implement enterprise data infrastructure solutions and create the blueprints for your organization’s data success.
Entity relationship diagrams, Relational Data Design, Online Analytical Processing, Operational Data Stores, Data Lake Architecture, Data Governance
Intermediate Python, SQL, and Basics of ETL/Data Pipelines
What does a data scientist do? In this course, we will survey the main topics in data science so you can understand the skills that are needed to become a data scientist!
Data Analysis Process, pandas (Python package), MapReduce paradigm
Explore a variety of datasets, posing and answering your own questions about each. You'll be using the Python libraries NumPy, Pandas, and Matplotlib.
Data Analysis, Python, numpy, pandas
Learn to use Structured Query Language (SQL) to extract and analyze data stored in databases
Mode
This course presents an example of applying a database application development methodology to a major real-world project.
Database Management Systems, Relational Algebra, Sequential Query Language, Data Indexing, SQL Injection
Georgia Institute of Technology
Intro to Inferential Statistics will teach you how to test your hypotheses and begin to make predictions based on statistical results drawn from data!
Inferential Statistics, Hypothesis Testing, T-tests, ANOVA
Master how to work with big data and build machine learning models at scale using Spark!
Spark, SparkSQL, Spark Dataframes, Data Wrangling, Machine Learning
Insight
This course will introduce students to the field by covering state-of-the-art modeling, analysis and visualization techniques.
R, Data Analysis, Data Visualization, Regression
Georgia Institute of Technology