Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineering 195

Data Engineering Data Engineering Data Engineering Data Engineer 195

Women in Big Data

OCTOBER 9, 2024

Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts. Data Processing (Preparation): Ingested data undergoes processing to ensure it’s suitable for storage and analysis.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Mlearning.ai

MAY 23, 2023

A good course to upskill in this area is — Machine Learning Specialization Data Visualization The ability to effectively communicate insights through data visualization is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 20, 2023

Descriptive Analytics Projects: These projects focus on summarizing historical data to gain insights into past trends and patterns. Examples include generating reports, dashboards, and data visualizations to understand business performance, customer behavior, or operational efficiency.

Analytics 40

Analytics Analytics Big Data Big Data 40

Data Science Dojo

MAY 24, 2024

Navigate through 6 Popular Python Libraries for Data Science R R is another important language, particularly valued in statistics and data analysis, making it useful for AI applications that require intensive data processing. C++ C++ is essential for AI engineering due to its efficiency and control over system resources.

AI 195

AI AI Deep Learning Deep Learning 195