Data

Lynda – 15 Mistakes to Avoid in Data Science

15 Mistakes to Avoid in Data Science
English | Size: 358.9 MB
Category: Tutorial


As a data scientist, your goal is to always be growing your skills. But, if you realize it or not, there are errors you may be making that are keeping you from moving to the next level. In this course, learn the top 15 data science mistakes: misunderstanding business problems, using the wrong tools, starting without a plan, and much more. Four leading data scientists share the hard-won lessons they’ve learned about alienating colleagues with technical jargon, moving too fast, and using sample sizes that are just too small. Find out why you should make your best effort to prevent bias-and avoid overpromising solutions to stakeholders. Plus, learn why writing custom code can lead to a big waste of time and why the most promising data science insights fall flat without a compelling story.

PluralSight Storing Data in HTML Bookware-KNiSO

PluralSight Storing Data in HTML Bookware-KNiSO
English | Size: 61.74 MB
Category: Tutorial


Sometimes you might need to store a small piece of user data without utilizing a database. This course will teach you how to store data in HTML without the use of a database

Data Camp – Data Engineer with Python [Career Track]

[FreeCoursesOnline.Me] Data Camp – Data Engineer with Python [Career Track]
English | Size: 5.62 GB
Category: Tutorial


In this track, you’ll discover how to build an effective data architecture, streamline data processing, and maintain large-scale data systems. In addition to working with Python, you’ll also grow your language skills as you work with Shell, SQL, and Scala, to create data engineering pipelines, automate common file system tasks, and build a high-performance database.

Udacity – Data Streaming Nanodegree – V1.0.0

Udacity – Data Streaming Nanodegree – V1.0.0
English | Size: 1.48 GB
Category: Tutorial


Learn how to process data in real-time by building fluency in modern data engineering tools, such as Apache Spark, Kafka, Spark Streaming, and Kafka Streaming. You’ll start by understanding the components of data streaming systems. You’ll then build a real-time analytics application. Students will also compile data and run analytics, as well as draw insights from reports generated by the streaming console.

Python Data Analysis with Pandas Library [UdemyLibrary.com]

Python Data Analysis with Pandas Library [UdemyLibrary.com]
English | Size: 1.65 GB
Category: Tutorial


Python programming has become one of the most sought after programming languages in the world, with its extensive amount of features and the sheer amount of productivity it provides. Therefore, being able to code Pandas in Python, enables you to tap into the power of the various other features and libraries which will use with Python. Some of these libraries are NumPy, SciPy, MatPlotLib, etc.