Instructors: Ed Spot
7 sections • 27 lectures • 1h 57m total length
Video: MP4 1280x720 44 KHz | English + Sub
Updated 7/2022 | Size: 880 MB

Last updated 9/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 302.71 MB | Duration: 0h 40m
A practical Hands-on Data Science Project on Graduate Admission Prediction Using Machine Learning

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 09/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 15 Lessons (4h) | Size: 3.38 GB
Mind-Blowing Science is back! Season 2 of our National Capital Emmy® Award-winning series has arrived and it's chock full of even more mind-blowing moments as a new batch of Scientific American's most intriguing articles are brought to life. For those who are not already familiar with the venerable publication Scientific American,...

Released 09/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 1h 1m | Size: 336 MB
If you're looking to improve how you attract, retain, and develop employees, people analytics can be one of the most compelling and effective ways to leverage the full power of data within your organization. In this course, instructor Serena Huang shows you how to use people analytics to optimize your talent acquisition and retention strategies.

Released 09/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 53m | Size: 180 MB
The larger and more complex the world of data science becomes, the more data there is to collect, sort, clean, model on, and much more. An emerging pain point in this brave new world is that a lot can go wrong if your data engineering and development practices are shoddy. This advanced-level course shows data scientists, Python developers, and data analysts how to test scientific (data science) code written in Python. Veteran data science trainer and consultant Miki Tebeka covers testing techniques, with a focus on issues specific to data science code, such as floating point errors, statistical testing, working with large datasets, choosing a baseline, and more. After presenting a testing overview, Miki dives into testing with pytest and hypothesis. He explains how to use schemas, truth values, approximate testing, and more in data validation. Miki goes over regression testing, then demonstrates how to test Jupyter Notebooks.

Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 393.61 MB | Duration: 0h 43m
It will help you learning science topics such as states of matter in brief with assignments and experiments.

Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.91 GB | Duration: 8h 1m
Earth Science Class Overview and Review