In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
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Excel Basics for Data Analysis
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Prepare Data for Exploration
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Databases and SQL for Data Science with Python
Data Science Methodology
Ask Questions to Make Data-Driven Decisions
Process Data from Dirty to Clean
Data Analysis with R Programming
Foundations: Data, Data, Everywhere
Data Visualization and Dashboards with Excel and Cognos
Tools for Data Science
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CoComelon
SS 2 Mathematics
Primary 3 Mathematics
Primary 1 Mathematics
ABC Songs for Kids - CoComelon Nursery Rhymes
Masha and the Bear 📱 Shorts!
Primary 2 English
التعليقات
10 تعليق
Linking GitHub to Watsonx Studio
Linking GitHub to Watsonx Studio
Linking GitHub to Watsonx Studio
Linking GitHub to Watsonx Studio
Jupyter Notebooks in Watsonx - Part 2
Jupyter Notebooks in Watsonx - Part 2
Jupyter Notebooks in Watsonx - Part 2
Jupyter Notebooks in Watsonx - Part 2
Jupyter Notebooks in Watsonx - Part 1
Jupyter Notebooks in Watsonx - Part 1
