Best Big Data Courses for Beginners to Ace the Technology

These Big Data Courses will Help you get High Paying Jobs.

Big data, is a valuable technology for industries all across the globe. Tech giants like eBay, NASA, Amazon, Google, and Facebook use big data to make better business decisions and get a sense of all the available data. If you are a tech enthusiast who wants to get a high-paying career in the tech world, big data is a lucrative field.

If you're a beginner, here are the best big data courses for you to get started.

1. Big Data Analytics

Duration: 10 weeks

This course will teach you essential skills in today's digital age to store, process, and analyze data to inform business decisions. This course will cover topics ranging from cloud-based big data analysis, predictive analytics including probabilistic and statistical models, application of large-scale data analysis, and analysis of problem space and data needs. By the end of this course, you will be able to approach large-scale data science problems with creativity and initiative.

2. Big Data and Hadoop

Through this course, you will understand the complex architecture of Hadoop and its components. It covers everything that you need as a Big Data Beginner, such as the Big Data market, different job roles, technology trends, history of Hadoop, HDFS, Hadoop Ecosystem, Hive, and Pig. This course also comes with a lot of hands-on examples that will help you learn Hadoop quickly.

3. Introduction to Big Data

This course is for tech enthusiasts who want to learn data science and are interested in understanding why the Big Data Era has become prominent. Through this course, you will learn about big data landscapes and real-world big data problems, important aspects of big data like volume, velocity, valence, value, and how they impact data collection, monitoring, storage, analysis, and reporting. This beginner needs no prior programming experience.

4. IoT Programming and Big Data

Duration: 5 Weeks

This course will teach you the introductory programming concepts that will help you understand IoT devices using the Python programming language. In addition, you will learn how to use Python to process text log files, such as those generated automatically by IoT sensors and other network-connected systems. No prior programming experience is required to enroll in this course.

5. Data Engineering Foundations

This course will take you through the fundamentals of data engineering. With a range of topics like data wrangling, database schema, and developing ETL pipelines, you will also experience several data engineering tools like Hive, Hadoop, Spark, and Airflow. By the end of this course, you will know the scope of data engineering in a data-driven organization.

6. Big Data in the Age of AI

Big data builds the foundations for many disruptive technologies that are crucial for businesses like AI and machine learning. In this non-technical course, you will learn how big data is shaping our data-driven world. Further, this course also digs into big data's connection with AI, data science, social media, IoT, and ethical issues behind data.

7. Foundations for Big Data Analysis with SQL

This course will show you the big picture of using SQL for big data, starting with an overview of data, database systems, and the common querying language (SQL). By the end of this course, you will be able to distinguish operational from analytic databases and understand how these are applied in big data, understand how database and table design provides structures for working with data, appreciate how differences in volume and variety of data affect your choice of an appropriate database system, recognize the features and benefits of SQL dialects designed to work with big data systems for storage and analysis, and explore databases and tables in a big data platform.

8. Data Ethics, AI, and Responsible Innovation

Duration: 7 weeks

In a world where we are surrounded by data, it is important to know how much control data has over us and vice versa. In this course, you will understand the ethical issues in the data lifecycle, learn about digital rights, data governance, responsible research, innovation, and apply critical judgment to solve moral problems with clear solutions.

9. Computational Thinking and Big Data

Duration: 10 weeks

Computational thinking is a skill that is critical for several industries to formulate a problem and express solutions for computers to work on. In this course, you will understand and apply advanced core computational thinking concepts to large-scale data sets, use industry-level tools for data preparation and visualization, such as R and Java, apply methods for data preparation to large data sets, understand mathematical and statistical techniques for attracting information from large data sets and illuminating relationships between data sets.

10. Taming Big Data with Apache Spark and Python

This course will teach you the hottest big data technology, Apache Spark. You will learn the concepts of Spark's DataFrames and Resilient Distributed, develop and run Spark jobs quickly using Python, translate complex analysis problems into iterative or multi-stage Spark scripts, scale up to larger data sets using Amazon's Elastic MapReduce service, understand how Hadoop YARN distributes Spark across computing clusters, and learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX.