Dataconomy

JULY 24, 2023

It involves developing algorithms that can learn from and make predictions or decisions based on data. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital. Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Pickl AI

APRIL 3, 2025

Modeling: Build a logistic regression or decision tree model to predict the likelihood of a customer churning based on various factors. Tools Commonly Used Business Intelligence Platforms: Tableau, Microsoft Power BI, Qlik Sense, Google Data Studio (Looker Studio) Programming Libraries: Matplotlib, Seaborn (Python); ggplot2 (R); D3.js

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Pickl AI

DECEMBER 4, 2024

Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees. Learn to use tools like Tableau, Power BI, or Matplotlib to create compelling visual representations of data. Additionally, familiarity with cloud platforms (e.g.,

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

What are the advantages and disadvantages of decision trees ? Yes, I am proficient in data visualisation tools such as Tableau, Power BI, and Matplotlib in Python, which I use to create interactive and insightful visualisations for data analysis. Lifetime access to updated learning materials.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 9, 2024

Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data. Visualisation Tools Familiarity with tools such as Tableau, Power BI, and D3.js js for creating interactive visualisations.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

ODSC - Open Data Science

JANUARY 7, 2025

Luckily, nothing too complicated is needed, as Tableau is user-friendly while matplotlib is the popular Python library for data visualization. Power BI is surprisingly popular as well, possibly for its focus on business and applications, making it more commonly used by even non-tech-savvy individuals.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40