How to Learn Machine Learning

APRIL 26, 2025

Data scientists try multiple models, evaluate their performance, and fine-tune some parameters to get better accuracy. Data Visualization and Interpretation To make the data understandable to stakeholders, visualizations are created in the form of charts, graphs, and dashboards.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Analytics and Data Analysis Coming in as the 4th most sought-after skill is data analytics, as many data scientists will be expected to do some analysis in their careers. This doesn’t mean anything too complicated, but could range from basic Excel work to more advanced reporting to be used for data visualization later on.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

For example, business analysts can use BI dashboards to conduct in-depth business analytics and visualize key performance metrics compiled from relevant datasets. They may also use tools such as Excel to sort, calculate and visualize data.

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Pickl AI

MARCH 20, 2024

Aspiring Data Scientists must equip themselves with a diverse skill set encompassing technical expertise, analytical prowess, and domain knowledge. Whether you’re venturing into machine learning, predictive analytics, or data visualization, honing the following top Data Science skills is essential for success.

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ODSC - Open Data Science

APRIL 3, 2023

As you’ll see below, however, a growing number of data analytics platforms, skills, and frameworks have altered the traditional view of what a data analyst is. Data Presentation: Communication Skills, Data Visualization Any good data analyst can go beyond just number crunching.

Analytics 52

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ODSC - Open Data Science

APRIL 6, 2023

This allows for it to be integrated with many different tools and technologies to improve data management and analysis workflows. One set of tools that are becoming more important in our data-driven world is BI tools. Think of Tableau, Power BI, and QlikView.

SQL 98

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Pickl AI

AUGUST 9, 2024

Data Cleaning and Transformation Techniques for preprocessing data to ensure quality and consistency, including handling missing values, outliers, and data type conversions. Students should learn about data wrangling and the importance of data quality. js for creating interactive visualisations.

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