ODSC - Open Data Science

APRIL 6, 2023

Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL. But why is SQL, or Structured Query Language , so important to learn? Let’s start with the first clause often learned by new SQL users, the WHERE clause.

SQL 98

SQL Data Scientist Database Data Science 98

How to Learn Machine Learning

APRIL 26, 2025

Data can be generated from databases, sensors, social media platforms, APIs, logs, and web scraping. Data can be in structured (like tables in databases), semi-structured (like XML or JSON), or unstructured (like text, audio, and images) form. Deployment and Monitoring Once a model is built, it is moved to production.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Tools and Techniques Commonly Used Data Analysts rely on various tools to streamline their work. Software like Microsoft Excel and SQL helps them manipulate and query data efficiently. They use data visualisation tools like Tableau and Power BI to create compelling reports.

Data Analyst 110

Data Analyst SQL Python AWS 110

Pickl AI

APRIL 10, 2023

Data Analysis is one of the most crucial tasks for business organisations today. SQL or Structured Query Language has a significant role to play in conducting practical Data Analysis. That’s where SQL comes in, enabling data analysts to extract, manipulate and analyse data from multiple sources.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

Pickl AI

JANUARY 25, 2023

The easiest skill that a Data Science aspirant might develop is SQL. Management and storage of Data in businesses require the use of a Database Management System. This blog would an introduction to SQL for Data Science which would cover important aspects of SQL, its need in Data Science, and features and applications of SQL.

SQL 52

SQL Data Science Database Data Analysis 52

Pickl AI

APRIL 21, 2025

This is where Big Data often comes into play as the source material. Cleaning and Preparing the Data (Data Wrangling) Raw data is almost always messy. Key Skills for Data Science: A data scientist typically needs a blend of skills: Mathematics and Statistics: To understand the theoretical underpinnings of models.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

ODSC - Open Data Science

FEBRUARY 2, 2023

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL are expected, you’ll need to go beyond that. Big Data As datasets become larger and more complex, knowing how to work with them will be key.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98