ODSC - Open Data Science

DECEMBER 7, 2023

Data Wrangling with Python Sheamus McGovern | CEO at ODSC | Software Architect, Data Engineer, and AI Expert Data wrangling is the cornerstone of any data-driven project, and Python stands as one of the most powerful tools in this domain.

Data Wrangling 98

Data Wrangling Data Science Machine Learning Machine Learning 98

Pickl AI

MARCH 20, 2024

Essential technical skills Understanding of statistics and probability A strong foundation in statistics and probability theory forms the bedrock of Data Science. R, with its robust statistical capabilities, remains a popular choice for statistical analysis and data visualization.

Data Science 52

Data Science Data Scientist Data Wrangling Data Visualization 52

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Explain the concept of feature engineering in Maachine Learning.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Dataconomy

MAY 16, 2023

Skills and qualifications required for the role Data scientists require a diverse set of skills and qualifications to excel in their role. Programming skills: Data scientists should be proficient in programming languages such as Python, R, or SQL to manipulate and analyze data, automate processes, and develop statistical models.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

AUGUST 21, 2023

Software engineering concepts facilitate efficient data manipulation, enabling you to design algorithms, create visualizations, and build machine learning models. Step 2: Acquiring Statistical Proficiency A Data Scientist’s toolkit is incomplete without a solid understanding of statistics.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

MAY 31, 2023

Accordingly, you need to make sense of the data that you derive from the various sources for which knowledge in probability, hypothesis testing, regression analysis is important. Statistical skills: having a clear idea regarding the procedures of different tasks requires you to have a thorough understanding of statistics.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

learn data science

OCTOBER 12, 2020

Summary View Analytics Chart Data Wrangling Dashboard Parameter Summary View Reference lines for Mean & Midian Now you can see the mean and the median values as reference lines on top of the histogram charts for numerical columns. I’m super excited to announce Exploratory v6.2! ??? Typically, you use P-Value as the threshold.

Data Wrangling 52

Data Wrangling Hypothesis Testing Analytics Analytics 52