MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 31m | Size: 399 MB
If you're looking for work as a junior data analyst, engineer, or scientist, this course gives you the best techniques to land jobs in data science. Instructor Ben Sullins explores a hiring manager's mindset and shows you how to prepare a demo that you can bring to your job interview. Ben explains some best practices for being physically and mentally healthy and well-prepared for your interview. He covers what to bring to your interview, then goes over follow-up methods and steps you should take to negotiate what you want most from an offer. Ben's methods give you the confidence and practice that you need to land a job in data science.

Duration: 1h 24m | Video: 1280x720 30 fps | Audio: AAC, 48 KHz, 2 Ch | Size: 483 MB
Skill Level: Intermediate | Genre: eLearning | Language: English
In the era of big data and data science, data governance has the ability to help all types of organizations and individuals become more successful. In this course, Dr. Jonathan Reichental introduces the topic of data governance in terms that everyone can understand, and helps you discover why your organization may benefit from data governance, how it's implemented, and why it is essential in compliance and risk reduction efforts. Jonathan also covers the role of data governance in emerging technology areas such as knowledge graphs, artificial intelligence, and the Internet of Things. In the last part of the course, he shares ideas on how organizations should think about managing, monitoring, and measuring data governance efforts.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 29m | Size: 337.7 MB
Are you considering working in data science, and would you like to try out some popular tools first? This course focuses on what you can do with Apache Spark. Instructor Ben Sullins shows you how to set up Spark on Databricks. Ben goes over how to import your data and start working with it, using both Python and SQL languages in Spark. He steps through taking your project to the next level with some easy data visualizations. After explaining some tips and tricks to present your data using Spark, Ben concludes with some additional resources that you can use to pursue your data science journey.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate| Genre: eLearning | Language: English + srt | Duration: 27m | Size: 292.1 MB
Python is a popular programming language in the field of data science, used for engineering and analytics, as well as data science itself. In this course, instructor Ben Sullins focuses on teaching you how to use Python using notebooks set up on the Jupyter platform. Ben walks through installing Jupyter using Anaconda, then shows you how to navigate the user interface and get Python running on a notebook in Jupyter. He covers how to import pandas, use pandas to explore sample data, and use data frames. Ben steps you through a number of functions, then concludes with some of the unique ways to present your data using Jupyter notebooks and Python.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 1m | Size: 638.9 MB
If you're interested in working in data or looking to advance in the field, you need a foundational knowledge of several key areas of data science. Not only that, you need to be able to demonstrate that knowledge. In this four-part series, Ben Sullins shows how to build four distinct data science projects using SQL, Tableau, Python, and Spark. In this second installment, Ben details the steps in building a sales dashboard with Tableau, the popular data visualization platform favored by organizations worldwide. Ben starts by breaking down the different aspects of Tableau, from working on a desktop, to sharing data over the web, to using the Tableau Public platform to publicly share your data visualizations. He then shows Tableau in action, looking at how it facilitates a deep dive into your data, before demonstrating how to build out an exploratory dashboard with your data. At the end of the course, you'll be able to give a live demo of your data visualizations in Tableau Public on the web.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 44m | Size: 509.9 MB
If you're interested in working in the field of data or looking to advance in the field, you need a foundational knowledge of several key areas of data science. Not only that, you need to be able to demonstrate that knowledge. In this four-part, hands-on series, Ben Sullins shows how to build four distinct data science projects using SQL, Tableau, Python, and Spark. In this first installment, Ben uses SQL to analyze employee data, which is notoriously difficult to analyze given its structure. He breaks down the specific structure of employee data, and the best way to track this kind of information, then covers how you can start answering specific questions utilizing SQL. Finally, he gives advice on how to present your data, considering both your audience and the visuals you use, in order to convey your knowledge of the subject.

English | 2021 | ISBN: 9798201285128 | 102 pages | PDF,EPUB | 0.75 MB
Knowing the data generated by your business every day is a key to success in the Data Analytic World that you are competing in. As there is so much data so, the organizations need to collect and store them. The data becomes valuable to businesses when it is analyzed.

English | 2021 | ISBN: 1801074151 | 407 pages | True (PDF EPUB) + Code | 77.63 MB
Make informed decisions using data analytics, machine learning, and data visualizations

English | 2020 | ISBN: 981120473X | 458 pages | True PDF | 19.43 MB
This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 13.2 GB | Duration: 24h 22m
What you'll learn