Navicat Data Modeler Premium 3.2.4 | 125.4 Mb
Navicat Data Modeler is a powerful and cost-effective database design tool which helps you build high-quality conceptual, logical and physical data models. It allows you to visually design database structures, perform reverse/forward engineering processes, import models from ODBC data sources, generate complex SQL/DDL, print models to files, and much more.

Aiseesoft FoneLab iPhone Data Recovery 10.3.88 (x64) Multilingual | 53.4 Mb
Safely and Easily Recover Lost Data from iPhone, iTunes and iCloud. Recover Text Messages, iMessages, Photos, Contacts, WhatsApp/Kik/Line/Viber/Facebook Messenger Data, Notes, Call History, etc.

Apeaksoft iPhone Data Recovery 1.2.12 | macOS | 64 mb
Apeaksoft iPhone Data Recovery gives you flexible solutions to recover lost data from any iPhone, iPad and iPod, including the latest iOS 16. You can use it to restore lost/deleted data caused by various reasons, like system crash, factory reset and iPhone lost/stolen. And its 80% recovering rate makes it more excellent than other tools.

Instructors: 247 Learning
4 sections • 22 lectures • 1h 59m total length
Video: MP4 1280x720 44 KHz | English + Sub
Updated 11/2022 | Size: 570 MB

Released: 11/2018
Duration: 39m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 81 MB
Level: Intermediate | Genre: eLearning | Language: English
Predictive analytics use historic data to look forward, enabling organizations to make better decisions. However, making accurate predictions from big data can be an overwhelming task. Enter Google Cloud Platform (GCP), a suite of cloud-computing services that bring scalability, elasticity, and automated machine learning to predictive analytics. This course—one of a series by data scientist Kumaran Ponnambalam—shows how to apply the power of GCP to generate predictions for your business. Start off by exploring the different tools and features for predictive analytics in GCP, including Cloud Dataproc, Cloud ML Engine, and the machine learning APIs such as Cloud Translation, Cloud Vision, and Cloud Video Intelligence. Then explore learn how to build, train, and deploy models to create predictions. Plus, learn best practices for cost control, testing, and performance monitoring of predictive models.

Released: 11/2018
Duration: 57m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 134 MB
Level: Intermediate | Genre: eLearning | Language: English
Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to conduct exploratory data analytics with GCP. First, review the concepts of segmentation and profiling. Then get hands on, as you learn to perform both text and visual analysis of data using tools provided by GCP: Cloud Datalab, BigQuery, Cloud Dataflow, and Data Studio. Finally, look at an end-to-end use case that applies what you've learned in the course.

Released: 09/2018
Duration: 1h | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 134 MB
Level: Intermediate | Genre: eLearning | Language: English
Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by veteran cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to design and build data warehouses using GCP. Explore the different types of storage options available in GCP for files, relational data, documents, and big data, including Cloud SQL, Cloud Bigtable, and Cloud BigQuery. Then learn how to use one solution, BigQuery, to perform data storage and query operations, and review advanced use cases, such as working with partition tables and external data sources. Finally, learn best practices for table design, storage and query optimization, and monitoring of data warehouses in BigQuery.

Released: 09/2019
Duration: 2h 7m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 309 MB
Level: Beginner | Genre: eLearning | Language: English
The hype about big data may have peaked several years ago, but big data is far from gone. Instead it forms the foundation for some of today's most exciting technologies. Artificial intelligence (AI), machine learning, and data science rely on big data, or data that—by virtue of its velocity, volume, or variety—can't be easily stored or analyzed with traditional methods. In this nontechnical course, Barton Poulson digs into the topic of big data, explaining how it works and shapes our modern data universe. Barton explains big data's relationship to AI, data science, social media, and the Internet of Things (IoT). He goes over some of the ethical issues behind the use of big data. Plus, he covers techniques involved in analyzing big data, including data mining and predictive analytics.

Instructors: Bluelime Learning Solutions
3 sections • 27 lectures • 1h 57m total length
Video: MP4 1280x720 44 KHz | English + Sub
Updated 10/2022 | Size: 760 MB

Instructors: 247 Learning
2 sections • 23 lectures • 1h 48m total length
Video: MP4 1280x720 44 KHz | English + Sub
Updated 11/2022 | Size: 474 MB