Best Big Data Courses For Beginners At The Cutting Edge Of Technology
by Apoorva Komarraju
July 2, 2021
These Big Data courses will help you get good paying jobs.
Big Data is a valuable technology for industries around the world. Tech giants like eBay, NASA, Amazon, Google, and Facebook are using big data to make better business decisions and get a feel for all the data available. If you’re a tech enthusiast who wants 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 to get you started.
Duration: 10 weeks
This course will teach you the 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 analytics, predictive analytics including probabilistic and statistical models, application of large-scale data analytics, and data analysis. problematic space and data needs. By the end of this course, you will be able to tackle large-scale data science problems with creativity and initiative.
Through this course, you will understand the complex architecture of Hadoop and its components. It covers everything you need as a big data newbie like big data market, different jobs, tech trends, history of Hadoop, HDFS, Hadoop Ecosystem, Hive and Pig. This course also includes many practical examples that will help you learn Hadoop quickly.
This course is for tech enthusiasts who want to learn data science and want to understand why the era of big data has become important. Through this course, you will learn about big data landscapes and real world big data issues, important aspects of big data such as volume, speed, valence, value and their impact on collection, monitoring , storage, analysis and reporting of data. This beginner does not need any prior programming experience.
Duration: 5 weeks
This course will teach you introductory programming concepts that will help you understand IoT devices using the Python programming language. Additionally, you will learn how to use Python to process text log files, such as those generated automatically by IoT sensors and other systems connected to the network. No previous programming experience is required to register for this course.
This course will introduce you to the basics of data engineering. Along with a range of topics such as data management, database schema, and ETL pipeline development, you will also learn about several data engineering tools such as Hive, Hadoop, Spark, and Airflow. By the end of this course, you will know the scope of data engineering in a data-driven organization.
Big Data lays the foundation for many disruptive technologies that are crucial for businesses such as AI and machine learning. In this non-technical course, you will learn how big data is shaping our data-driven world. In addition, this course also explores the connection of big data with AI, data science, social media, IoT, and the ethical issues behind data.
This course will show you an overview of using SQL for Big Data, starting with an overview of data, database systems, and Common Query Language (SQL). By the end of this course, you will be able to distinguish operational databases from analytical databases and understand how these are applied in big data, understand how database and table design provides insights 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.
Duration: 7 weeks
In a world where we are surrounded by data, it is important to know how much control the data has over us and vice versa. In this course, you will understand 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. .
Duration: 10 weeks
Computational thinking is an essential skill for many industries to formulate a problem and express solutions that computers need to work on. In this course, you will understand and apply advanced concepts of computational thinking to large-scale datasets, use industry-level tools for data preparation and visualization, such as R and Java, apply methods of preparing data data to large data sets, understand mathematics and statistical techniques to draw information from large data sets and illuminate relationships between data sets.
This course will teach you about the hottest big data technology, Apache Spark. You will learn the concepts of Spark’s DataFrames and Resilient Distributed, develop and run Spark tasks quickly using Python, translate complex analysis problems into iterative or multistep Spark scripts, upgrade to larger data sets Using Amazon’s Elastic MapReduce service, understand how Hadoop YARN distributes Spark across IT clusters and learn about other Spark technologies, such as Spark SQL, Spark Streaming, and GraphX.
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