-
Praneeth.Akondi started taking the course Probability & Statistics 2 days, 18 hours ago
Course
Probability & Statistics
This course provides learners with key Statistical concepts and will enable them to apply these concepts in their daily deliverable(s).
-
Praneeth.Akondi joined the group Probability & Statistics 2 days, 18 hours ago
-
Thanuja.Chirivella completed the lesson Spark RDDs 4 days, 1 hour ago
Lesson
Spark RDDs
-
Thanuja.Chirivella completed the lesson Getting Started with Spark and PySpark 4 days, 1 hour ago
Lesson
Getting Started with Spark and PySpark
-
Thanuja.Chirivella completed the topic References 4 days, 1 hour ago
-
Thanuja.Chirivella completed the topic Example: Basic PySpark Program 4 days, 1 hour ago
-
Thanuja.Chirivella completed the topic Driver Programs, SparkContext and Executors 4 days, 1 hour ago
-
Thanuja.Chirivella completed the topic Installing Spark and PySpark 4 days, 1 hour ago
-
Thanuja.Chirivella completed the topic References 4 days, 1 hour ago
-
Thanuja.Chirivella completed the lesson Introducing Spark 4 days, 1 hour ago
Lesson
Introducing Spark
-
Thanuja.Chirivella completed the topic Spark in the Industry 4 days, 1 hour ago
-
Thanuja.Chirivella completed the topic Why Spark? 4 days, 1 hour ago
-
Thanuja.Chirivella completed the lesson Pre-requisites 4 days, 2 hours ago
Lesson
Pre-requisites
-
utkarsh.raj completed the topic Extract, Transform & Load (ETL) 5 days, 1 hour ago
-
utkarsh.raj completed the topic References 6 days ago
-
utkarsh.raj completed the topic Cross Industry Standardization 6 days ago
-
utkarsh.raj completed the topic Data Source & Database 6 days ago
-
utkarsh.raj completed the topic Significance of Data 6 days ago
-
utkarsh.raj started taking the course Data Engineering: Level 01 6 days ago
Course
Data Engineering: Level 01
Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there must be mechanisms for collecting and validating that information. In order for that work to ultimately have any value, there also have to be mechanisms for applying it to real-world operations in some way. Those are both engineering tasks: the application of science to practical, functioning systems. Data engineers focus on the applications and harvesting of big data. Their role doesn’t include a great deal of analysis or experimental design. Instead, they are out where the rubber meets the road (literally, in the case of self-driving vehicles), creating interfaces and mechanisms for the flow and access of information.
-
utkarsh.raj joined the group Data Engineering: Level 01 6 days ago
- Load More