This Hadoop Fundamentals course is a perfect choice for those who want to gain the understanding of concepts like Big Data and Hadoop from the scratch.
Learning Style
Learning Style
Difficulty
Course Duration
This Hadoop Fundamentals course is a perfect choice for those who want to gain the understanding of concepts like Big Data and Hadoop from the scratch.
This course teaches about the Hadoop basic concepts. This Hadoop Fundamentals course is a perfect choice for those who want to gain the understanding of concepts like Big Data and Hadoop from the scratch. The course does not cover advanced level concepts though. However, by the end of this course, students will have an understanding of what goes behind the processing of huge volumes of data as the industry shifts from the excel-based analytics to real-time analytics.
Along with covering the basics of the program, the course will also give a general understanding of the commercial distributions of Hadoop alongside the features of the Hadoop ecosystem.
The course has the following learning objectives:
This course, Hadoop Fundamentals is intended for those experienced professionals who want to know the basics of Big Data and Hadoop. The course is extremely useful for those professionals who are on senior position in management and want to gain a theoretical comprehension of the way in which Hadoop can resolve their Big Data problem.
None.
| Subjects | Big Data |
|---|---|
| Lab Access | No |
| Technology | Hadoop |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Beginner |
| Course Duration | 3 Hours |
| Language | English |
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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