ODSC - Open Data Science

JANUARY 3, 2024

This course is perfect for people beginning their AI journey and provides valuable insights that we will build up in subsequent SQL, programming, and AI courses. Upon completion, students will have a strong foundation in SQL and be able to use it effectively to extract insights from data.

Data Wrangling 52

Data Wrangling Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

SEPTEMBER 1, 2023

It covers topics such as data collection, organization, profiling, and transformation as well as basic analysis. It will help you begin your AI journey and gain valuable insights that we will build up in subsequent SQL, programming, and AI courses. You will learn how to design and write SQL code to solve real-world problems.

Data Wrangling 52

Data Wrangling Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

AUGUST 15, 2023

Build Classification and Regression Models with Spark on AWS Suman Debnath | Principal Developer Advocate, Data Engineering | Amazon Web Services This immersive session will cover optimizing PySpark and best practices for Spark MLlib. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

Data Science 52

Data Science Machine Learning Machine Learning Data Scientist 52

Becoming Human

MAY 15, 2023

One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

MARCH 20, 2024

Proficiency in programming languages Fluency in programming languages such as Python, R, and SQL is indispensable for Data Scientists. These languages serve as powerful tools for data manipulation, analysis, and visualization.

Data Science 52

Data Science Data Scientist Data Wrangling Machine Learning 52

Dataconomy

MAY 16, 2023

Key skills and qualifications for data scientists include: Statistical analysis and modeling: Proficiency in statistical techniques, hypothesis testing, regression analysis, and predictive modeling is essential for data scientists to derive meaningful insights and build accurate models.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

JUNE 7, 2024

Comprehensive Data Management: Supports data movement, synchronisation, quality, and management. Scalability: Designed to handle large volumes of data efficiently. It offers connectors for extracting data from various sources, such as XML files, flat files, and relational databases. How to drop a database in SQL server?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40