
Master numpy for numerical computing in Python by creating, indexing, reshaping, and sorting 1D and 2D arrays, exploring data types, random matrices, diagonal and identity arrays, and core operations.
Explore plotting with two Python libraries, the map library and Seaborn, to create map plots, lines, subplots, distributions, and heat maps.
Apply exploratory data analysis to ensure data quality and guide model selection by identifying predictor and target variables, performing univariate and bivariate analyses, handling missing values, and transforming variables.
Do you want to learn the most important tools of Artificial intelligence and Machine Learning? Then we’ve got a perfectly designed course for you.
Artificial Intelligence has enabled the processing of a large number of data and its use in the domain. There are several tools, frameworks, and libraries available to data scientists and developers, but knowing when and how to use these tools is a must. This course on basic artificial intelligence tools will help you gain this knowledge practically.
Major Topics This Course Covers
Pandas and NumPy
Matplotlib and Seaborn
Scikit Learn and Scipy
Exploratory Data Analysis
To become a successful data scientist or developer, you need to master these above libraries. These AI libraries will help you build reliable AI projects. In this course, you'll learn how to use these tools to visualize data and prepare data sets for AI and machine learning projects.
You'll also learn how to use these tools to build projects from scratch. In this course, we'll be covering topics that will help you learn how to validate AI models and interpret models. The course curriculum features real examples that will help you learn all the tool features efficiently.
So why are you waiting now? Start your journey to become a complete AI specialist with this course!
See You In Class!