Seaborn Tutorial (3 Courses, 2+ Projects)

Objectives

The seaborn training comes up with lifetime access, online courses, includes hands-on projects that will help individuals to improve their knowledge and real-time scenarios and make them self-industry ready and what’s this training will be completed they will be awarded a variable certificate of completion that is the east all over the industry.

There are a variety of skills that participants will learn through this training program like visualizing statistical relationships, different types of visualizations, scatter plots, plotting with categorical data, bar plots, color palettes, visualizing linear relationships, bivariate distributions, univariate distributions, visualizing the distribution of a data set, cat plot, strike plot, etc.

What’s the training gets completed the learners can easily enter the industry as a data analyst, business analyst, statistician, quality engineer, quality manager, consultant, team leader, statistical analyst, software test engineer, QA engineer, consultant, analytics manager, and many other diverse fields are open for individuals to show their potential and skills in the world.

Course Highlights

As training goes ahead, individuals will start realizing the importance and value of sea born training with diverse skills and concepts that are going to be taught under this training program. The curriculum of the training program is developed in such a way that it helps in getting all the industry requirements and also take squares of individuals’ requirements who are investing their time and efforts in learning something new and interesting. The core skills that are going to be covered under this training program are as follows:

• One will learn about introduction to seaborn, o review of the training, different types of plots, distribution plot, scatterplot and heat map, case studies of scatter plot, boxplot, bank problem, case study on swarm plot, etc.
• Other skills that are going to be covered under this training program is visualizing statistical relationships which include scatterplots, line plots, plotting with categorical data, showing multiple relationships with facets, categorical scatter plots, distribution of observations with categories, statistical estimation with categories, count plot, point plot, boxplot, bar plot, use of reference files, etc.
• Under this part of the training program, advanced concepts of seaborn tool that are an introduction to seaborn advance, building structure multiplot grids, conditional small multiplies, use of custom functions, plotting pairwise data relationships, choosing color palettes, use of different seaborn figure styles, setting different color palettes, use of reference files in advance, etc.
• This part of the training program what we learn about intermediate functionalities of seaborn which includes plotting univariate distribution, clotting of bivariate distributions, visualizing linear relationships, functions to draw linear regression models, filtering different kinds of models, conditioning all other variables, join plot and LM plot, use of reference files, KDE plot, etc.
• One will learn about different types of visualizations, things to keep in mind before choosing the type of visualization, customizing visualizations, use of color palettes, etc which are going to be very useful skills that are very much in demand these days.

Project Highlights

With the use of projects, any sort of tradings or tutorial the efficiency of the training increases drastically is it provides a space for the learners to experiment and everywhere their knowledge in real-time scenarios which helps them understand the concepts in a better way. Different projects are involved in this training to increase the utility and efficiency of the program. Projects that are part of this training program are as follows:

• A project on data visualization using Census data that includes an introduction to the project, installation of the tools, installation of the libraries, exploratory data analysis, adding columns to the data set, data visualizations using scatter plots, multiple line plots, use of category imports, point plot, heat map, pair plot, I m plot, pair grid, violin plot, hot, x, and y tick label plot, and settings, swarm plot, etc.