Learn about the concept and importance of fundamental data science skills. Jungwoo emphasizes the ability to write code, use database management systems, leverage infrastructure software, take advantage of machine learning, and visualize data.
- To be a successful data scientist,…you first need to acquire…a baseline knowledge of statistics.…But since so much of the data industry is driven by IT,…it's also important for data scientists…to be well-versed in the underlying technologies…that support what they do on the job everyday.…These include the ability to write code…in languages such as Python or R…which come with powerful libraries…that implement statistical functions…as well as visualization features.…
Ability to program in general is invaluable.…A data scientist who is also a good programmer…can automate mundane but necessary tasks…and focus on solving larger problems.…Knowing how database management systems work…is another essential skill to master.…Whether structured or unstructured,…much of our data is stored in databases…and familiarity in Structured Query Language or SQL…is highly desired because it allows you…to interact with databases natively.…
Developing a good understanding…of data science infrastructure technologies…is important too.…Distributed file systems like Hadoop…
- Enabling technologies in data science
- Cloud computing and virtualization
- Installing and working with Proxmox, Hadoop, Spark, and Weka
- Managing virtual machines on Proxmox
- Distributed processing with Spark
- Fundamental applications of machine learning
- Distributed systems and distributed processing
- How Hadoop, Spark, and Weka can work together
Skill Level Beginner
Course organization1m 17s
1. Introduction to Data Science
2. Cloud Computing
3. Distributed File Systems
4. Distributed Processing
5. Machine Learning
6. Case Study
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