Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Smart Data Collective

OCTOBER 14, 2019

Businesses need software developers that can help ensure data is collected and efficiently stored. They’re looking to hire experienced data analysts, data scientists and data engineers. With big data careers in high demand, the required skillsets will include: Apache Hadoop. NoSQL and SQL.

Big Data 99

Big Data Big Data Apache Hadoop Hadoop 99

Pickl AI

MAY 29, 2024

Summary: Data Science is becoming a popular career choice. Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 28, 2023

If you’re an aspiring professional in the technological world and love to play with numbers and codes, you have two career paths- Data Analyst and Data Scientist. What are the critical differences between Data Analyst vs Data Scientist? Who is a Data Scientist? Let’s find out!

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 52

Pickl AI

MARCH 10, 2023

Data Science is the process in which collecting, analysing and interpreting large volumes of data helps solve complex business problems. A Data Scientist is responsible for analysing and interpreting the data, ensuring it provides valuable insights that help in decision-making.

Data Scientist 52

Data Scientist Data Science Apache Hadoop Machine Learning 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

NOVEMBER 4, 2024

Its robust ecosystem of libraries and frameworks tailored for Data Science, such as NumPy, Pandas, and Scikit-learn, contributes significantly to its popularity. Moreover, Python’s straightforward syntax allows Data Scientists to focus on problem-solving rather than grappling with complex code.

Data Science 52

Data Science Python Machine Learning Machine Learning 52