Big Data Certification

Top Big Data Certification Programs

Big data can be a key differentiator for businesses to remain competitive. In order to capitalize on new business opportunities, they need the skills and expertise to analyze big data. That’s where big data certification can come in handy. In this guide, you will learn about the top online programs to enroll in today.

Our Top 10 Picks

Udacity Logo
Data Architect Nanodegree
Best overall Big Data certification
University of Adelaide
MicroMasters® Program in Big Data
Best professional Big Data certification
Udacity Logo
Data Streaming Nanodegree
Best project-based Big Data courses
IBM
Professional Certificate in NoSQL, Big Data and Spark Fundamentals
Best beginner Big Data certificate
DataCamp
Big Data with PySpark Skill Track
Best hands-on Big Data courses
Dataquest
Spark and MapReduce
Best Apache Spark courses
Hong Kong University
MicroMasters® Program in Big Data Technology
Best program for experienced users
DataCamp
Big Data with R Skill Track
Best Big Data courses with R focus
Cloudera
Modern Big Data Analysis with SQL Specialization
Best SQL analysis courses
UC San Diego Logo
Big Data Analytics Using Spark
Best budget Big Data course

1. Data Architect Nanodegree (Udacity)

Udacity Logo

Get a career blueprint for data architecture, design, and implementation. In the Data Architect Nanodegree program, you will learn how to create, design, and implement enterprise-class data solutions.

In this nanodegree program, you’ll meet the needs for Big Data by building an Online Analytical Processing (OLAP) data model with components such as a relational database with PostgreSQL, data warehouses, and scalable data lake architecture.

Courses

  1. Data Architecture Foundations – Get a crash course in data architecture so you can design more efficient solutions. You’ll learn how to design data models, normalize data, and create a professional ERD. Finally, you’ll design and populate a database using PostgreSQL in this course project.
  2. Designing Data Systems – Take the first step in learning how to design enterprise data architecture with Snowflake and a data warehouse. This course covers designing an Operational Data Store (ODS), ELT data processing, and building reports with SQL queries.
  3. Big Data Systems – Learn how to design and implement big data solutions that can help your organization identify and solve Big Data problems.  First, you’ll familiarize yourself with tools like HDFS, MapReduce, Hive, and Spark for distributed storage.  Next, you will look into NoSQL databases such as Amazon DynamoDB.  Finally, you will implement a Data Lake with transactional capabilities.
  4. Data Governance – Get a handle on data management and governance so you can implement it into your business.  Overall, this course will help you to understand metadata, examine data quality through data profiling, and how to use golden record creation for data governance processes.

Skills Acquired

  • Big Data
  • PostgreSQL
  • Online Analytical Processing (OLAP)
  • Data Warehouse
  • Entity Relationship (ER) Diagram
  • Snowflake
  • Data Architecture
  • Operational Data Store
  • ELT
  • HDFS (Hadoop Distributed File System)
  • MapReduce
  • Hive and Spark
  • NoSQL Databases
  • Amazon DynamoDB
  • Data Lake Design
  • Metadata Management System
  • Enterprise Data Model
  • Data Governance
  • INFORMATION: This nanodegree program requires intermediate Python, SQL, and the basics of ETL/Data pipelines.

2. MicroMasters® Program in Big Data (University of Adelaide)

University of Adelaide

The exploding volume of data has created an opening for data scientists to drive greater visibility into their organizations’ data and rapid insights. The online MicroMasters® Program in Big Data from the University of Adelaide gives you the right skill sets to enter this cutting-edge field.

By enrolling in this online program, you will gain skills that will help you solve big data problems and improve your understanding of how big data works. It covers core concepts including its mathematical concepts and big data analytical tools like R and Java.

Courses

  1. Programming for Data Science – Learn how to solve real-world data science problems, from the ground up. We will guide you through the basics of programming, data analysis, and computation so that you can create powerful insights from data.
  2. Computational Thinking and Big Data – Take the first step in becoming a skilled computational thinker. This course will teach you the basics of data analysis, data cleaning, and data consolidation. You will learn how to use these techniques to solve complex problems.
  3. Big Data Fundamentals – Get a hands-on understanding of how big data is changing the way organizations function, and learn essential analytical tools and techniques that will help you make decisions that are most impactful.
  4. Big Data Analytics – Get the skills you need to analyze and understand large-scale data sets. This course will teach you how to use Apache Spark and R to extract valuable information from data sets.
  5. Big Data Capstone Project – Get the skills you need to apply big data to real-world problems. In this project, you will use your knowledge of big data to create a solution that involves data cleaning, regression, or classification.

Skills Acquired

  • Big Data
  • R (ggplot2)
  • Java
  • Data Abstraction
  • Storage
  • Decomposition
  • Pattern Recognition
  • Abstraction
  • Dimension Reduction
  • Bayesian Models
  • MapReduce
  • Hash Functions
  • Volume, Velocity, and Variety
  • Data Mining
  • Apache Spark
  • Linear Regression
  • Deep Learning Concepts
  • Data Cleaning
  • INFORMATION: This program contains 5 graduate-level courses that are self-paced for a one-year duration.

3. Data Streaming Nanodegree (Udacity)

Udacity Logo

Get the skills you need to build real-time applications that process big data at scale. The Data Streaming Nanodegree Program will teach you how to build stream-based applications using open-source frameworks and libraries.

Throughout the program, you will get up to speed with the latest data processing techniques in this 2-month nanodegree. Finally, you will learn how to build efficient techniques to process big data and build streaming applications with Apache Spark, Kafka, and Kafka Streaming.

Courses

  1. Foundations of Data Streaming – Get ahead of your data streaming challenges and learn the basics of stream processing. This essential course covers everything from data schemas to Kafka Connect to REST proxy, KSQL, and Faust Stream Processing.
  2. Streaming API Development and Documentation – This course aims to grow your expertise in streaming data systems, and build a real-time analytics application in Spark Streaming. During the project portion of this course, you will Kafka’s topic using Kafka Connect Redis Source for a working application.

Skills Acquired

  • Big Data
  • Apache Spark
  • Kafka
  • Spark Streaming
  • Kafka Streaming
  • Real-Time Analytics Applications
  • Data Streaming
  • ApacheAvro
  • Kafka Connect
  • REST Proxy
  • KSQL
  • Faust Stream Processing
  • Streaming API Development
  • DataFrames
  • Spark Clusters
  • Spark Structured Streaming
  • INFORMATION: This nanodegree program requires intermediate Python, SQL, and the basics of ETL/Data pipelines.

4. Professional Certificate in NoSQL, Big Data and Spark Fundamentals (IBM)

IBM

Get a Professional Certificate in NoSQL, Big Data, and Spark Fundamentals that will help you in your career and understand the basics of technologies like MongoDB, Cassandra, and IBM Cloudant.

First, you’ll get the skills you need to apply Big Data, data engineering, and ETL in a hands-on setting.  Finally, you’ll learn machine learning skills using k-means like regression, classification, and clustering.

Courses

  1. NoSQL Database Basics – Get started with MongoDB, Cassandra, and IBM Cloudant NoSQL databases in this comprehensive course. You will have hands-on skills for working with these databases and learn the basics of NoSQL database design.
  2. Big Data, Hadoop, and Spark Basics – Take your big data skills from theory to practice. Learn how to use Hadoop and Spark to analyze data and make insights.
  3. Apache Spark for Data Engineering and Machine Learning – Get up to speed with the basics of data engineering and machine learning. In this course, you will learn how to apply Spark skills to ETL and ML workflows using regression and classification.

Skills Acquired

  • Big Data
  • NoSQL
  • Apache Spark
  • MongoDB
  • Cassandra
  • IBM Cloudant
  • Hadoop (HDFS)
  • Hive
  • HBase
  • Resilient Distributed Datasets (RDDs)
  • DataFrames
  • SparkSQL
  • Catalyst
  • Tungsten
  • ETL
  • Spark Structured Streaming
  • GraphFrames
  • Data Cleaning
  • Regression + Classification
  • SparkML
  • K-means Algorithm
  • Kubernetes
  • IBM Watson Studio
  • INFORMATION: This program contains 4 skill-building courses that are self-paced for a four-month duration.

5. Big Data with PySpark Skill Track (DataCamp)

DataCamp

Take your data science skills to the next level and use PySpark to power high-performance machine learning models. Explore the powerful parallel compute capabilities of Spark with the Big Data with PySpark Skill Track from DataCamp.

With Apache Spark, you get the power to process massive data sets quickly with end-to-end workflows. You can use this data to train models, create recommendations, and more. DataCamp has a much more hands-on approach to learning so this is really worth checking out.

Courses

  1. Introduction to PySpark – Start learning how to use PySpark to manage and analyze data in Spark. This course will teach you the basics of data science and machine learning, and show you how to apply these skills to real-world problems.
  2. Big Data Fundamentals with PySpark – Learn the basics of big data analytics with PySpark. This course will teach you how to work with large data sets, use data analysis tools, and apply machine learning to improve your business.
  3. Cleaning Data with PySpark – Get a deeper understanding of data cleaning with our PySpark course. You will learn how to clean data using Apache Spark and improve performance.
  4. Feature Engineering with PySpark – Get the skills you need to get the most out of your data using PySpark. This course is designed for data scientists who want to work with data wrangling and feature engineering.
  5. Machine Learning with PySpark – Get a grip on the basics of machine learning and predictive modeling with this machine learning course. With this course, you will be able to predict outcomes and make predictions for a range of scenarios in Apache Spark.
  6. Building Recommendation Engines with PySpark – Get started on building recommendation engines with PySpark. In this course, you will learn how to use Spark to build recommendations for positive user experiences.

Skills Acquired

  • Big Data
  • PySpark
  • Data Cleaning
  • Feature Engineering
  • Machine Learning
  • Recommendation Engines
  • Spark Python API
  • Distributed Data Management
  • Model Tuning
  • ML Pipelines
  • Logistic Regression
  • SparkSQL
  • Resilient Distributed Dataset (RDD)
  • MLlib
  • DataFrames
  • K-means Clustering
  • Python
  • Data Pipelines
  • Data Wrangling
  • Spark Functions
  • Ensembles & Pipelines
  • Classification
  • Regression
  • INFORMATION: This skill track contains 6 skill-building courses with 24+ hours of coursework.

6. Spark and MapReduce (Dataquest)

Dataquest

In the Spark and MapReduce course, you will learn how to use Spark and MapReduce to process a large variety of real-world data sets.

Throughout the program, you will learn how to use Spark to break down large data sets into manageable tasks. In addition, you will explore how to use MapReduce to process and transform these data sets.

Courses

  1. Introduction to Spark – This course will walk you through Apache Spark and how to use it to power your next big project. For example, you’ll learn Resilient Distributed Data Sets (RDDs), lazy evaluation, and pipelines.
  2. Project: Spark Installation and Jupyter Notebook Integration – This project will test how to install Apache Spark and integrate it with Jupyter Notebook.
  3. Transformations and Actions – Get the most out of your data by using Spark transformations and actions to manage your RDD data in the most efficient way.
  4. Challenge: Transforming Hamlet into a Data Set – You’ll transform text from Hamlet into a usable form for data analysis.
  5. Spark DataFrames – Learn about reading in data, schemas, filtering, and row objects in Apache Spark DataFrames.
  6. Spark SQL – Continue your data science journey with this Spark SQL Course. With this course, you will learn Spark SQL, the data analysis tool that powers the Apache Spark ecosystem.

Skills Acquired

  • Big Data
  • Spark
  • MapReduce
  • DataFrames
  • Spark SQL
  • Lazy Evaluation
  • Pipelines
  • Scala
  • Jupyter Notebooks
  • Map + FlatMap Methods
  • Pandas
  • Row Objects
  • INFORMATION: This skill track contains 6 skill-building courses with 6+ hours of coursework.

7. MicroMasters® Program in Big Data Technology (Hong Kong University of Science and Technology)

Hong Kong University Science and Technology

Gain a better understanding of complex data and make better decisions.  With the help of the MicroMasters® Program in Big Data Technology, you will be able to identify and solve big data integration and storage problems.

Get the most out of big data by investigating data issues and finding solutions. By the end of this 9-month program, you will be able to take control of your data, get insights, and make changes to your business processes with the help of Big Data technology.

Courses

  1. Foundations of Data Analytics – Get fully equipped to learn how to use big data technologies and analyze data to achieve business goals. This data analytics course will give you the foundational skills you need to be successful in data analytics.
  2. Data Mining and Knowledge Discovery – Get your data mining skills on point so that you can find and extract the valuable knowledge it contains. This course will teach you classification techniques, pattern mining, data warehouses, and much more.
  3. Big Data Computing with Spark – Gain the knowledge and skills you need to understand and use big data systems such as Hadoop and Spark.
  4. Mathematical Methods for Data Analysis – Learn how to use mathematical methods to analyze data and make insights. This course will introduce you to some well-known machine learning algorithms, such as k-means, and help you understand their mathematical formulations.
  5. Big Data Technology Capstone Project – You will be able to use the techniques and theory you have learned in these MicroMasters program courses to complete a medium-scale project.

Skills Acquired

  • Big Data
  • Big Data Analytics
  • Data Mining
  • Knowledge Discovery
  • Apache Spark
  • Mathematical Methods
  • Data Security
  • Python Libraries
  • Data Warehouse
  • Hadoop
  • GraphX/GraphFrames
  • SparkStreaming
  • Resilient Distributed Dataset (RDD)
  • MapReduce
  • Linear Transformations
  • INFORMATION: This MicroMasters® Program contains 5 graduate-level courses over a period of 9 months.

8. Big Data with R Skill Track (DataCamp)

DataCamp

Get a first-hand understanding of how to work with Big Data in R, and see how Spark can be used to power your next project.

This Big Data with R Skill Track is perfect for students who are interested in data science and want to learn more about how to work with Big Data.

Courses

  1. Writing Efficient R Code – Get the skills you need to write efficient and reliable R code. In this course, you will learn all you need to know about benchmarking, profiling, and parallel programming.
  2. Visualizing Big Data with Trelliscope in R – Take your data visualization skills to the next level with this R course that covers how to use ggplot2 and Trelliscope to visualize data in a more understanding way.
  3. Scalable Data Processing in R – You will also learn how to use the bigmemory and iotools packages to speed up your data processing.
  4. Introduction to Spark with sparklyr in R – Get a handle on big data analysis with the help of Apache Spark, R, and the sparklyr package.

Skills Acquired

  • Big Data
  • R
  • Parallel Programming
  • TrelliscopeJS
  • ggplot2
  • Tidyverse
  • Scalable Data Processing
  • bigmemory
  • iotools
  • Apache Spark
  • sparklyr
  • dplyr
  • Spark DataFrames
  • INFORMATION: This skill track contains 4 skill-building courses with 16+ hours of coursework.

9. Modern Big Data Analysis with SQL Specialization (Cloudera)

Cloudera

This Modern Big Data Analysis with SQL Specialization will teach you how to use distributed SQL engines to query Big Data and master using SQL for data analysis.

Get the most out of your Big Data by using the latest SQL dialects designed to work with big data systems.  Finally, you will learn how to choose the most appropriate database system for your specific business needs.

Courses

  1. Foundations for Big Data Analysis with SQL – Learn how to use SQL to solve big data problems, from understanding the data to building models and analyzing the results. This course provides the foundation you need to work with big data in a real-world environment.
  2. Analyzing Big Data with SQL – In this course, you will learn how to analyze big data with SQL. You will understand how to use different SQL engines to analyze big data, including Apache Hive and Apache Impala.
  3. Managing Big Data in Clusters and Cloud Storage – Get a first-hand understanding of how to manage data in clusters and cloud storage, so you can unleash the power of big data for your business. This comprehensive course provides you with the skills and knowledge you need to get started in this growing field.

Skills Acquired

  • Big Data
  • SQL
  • Distributed Big Data Systems
  • Apache Impala
  • Apache Hive
  • SQL Dialects
  • MySQL + PostgreSQL
  • Big Data Clusters
  • Cloud Storage
  • Big Data Analysis
  • INFORMATION: This beginner-level specialization contains 3 skill-building courses over a period of 4 months.

10. Big Data Analytics Using Spark (UC San Diego)

UC San Diego

Get started with big data analytics today and learn how to use Spark to solve problems in a complex data set and machine learning methods. The Big Data Analytics Using Spark course from UC San Diego will teach you about PySpark, Parquet, and the Jupyter notebooks environment.

Throughout the course, you will learn how to find bottlenecks and optimize performance in Spark. By the end of this course, you will be able to process massive data sets using supervised and unsupervised machine learning techniques.

Skills Acquired

  • Big Data
  • Spark
  • PySpark
  • Parquet
  • Data Loading + Cleaning
  • Machine Learning
  • Statistical Methods
  • Jupyter Notebooks
  • MapReduce
  • Big Data Analytics
  • INFORMATION: This single course is free with 10 weeks of coursework and material.

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