This can be a super guide for you to start and excel in your data science career.
This can be a super guide for you to start and excel in your data science career.
This can be a super guide for you to start and excel in your data science career. A lot of times we are either bombarded with inadequate information/ content which is partially industry oriented. In most cases, the effectiveness of a professional is determined on the basis of his/her practical experience. That is why one’s skill development process should involve hands-on experience of tools and languages, knowledge of enough use cases, thirst of implementing your knowledge and experience for getting a job profile in Data Science.
The pillars of data science professionals are
We are here to directly help you in understanding, practicing and implementing formulas of excel to make business reports and dashboards.
Nearly 20 domain’s real business use cases will be available for you to study and explore.
Familiarity with SQL is a must. Getting your hands more dirty in SQL will make your pockets more wealthy. If you are completely new to SQL, then it’s not a problem because we think SQL is one of the easiest languages. We will let you think, play and solve hundreds of our customized SQL exercises according to level of proficiency required.
Visualize and materialize. There is not a better way to analyze something and then present it into some beautiful, interactive visualization reports or dashboards. Tableau, Google Data Studio, Power BI these will be your friends in the process.
To give a smooth finishing touch or to build an entire platform of any data science project, python is a needed arsenal. Our team has some of the best python programmers which can help you throw away fear of python coding and make you learn some interesting python skills.
ANCOVA is an extension of ANOVA (Analysis of Variance) that combines blocks of regression analysis and ANOVA. Which makes it Analysis of Covariance.
What if we learn topics in a desirable way!! What if we learn to write Python codes from gamers data !!
Start using NotebookLM today and embark on a smarter, more efficient learning journey!
This can be a super guide for you to start and excel in your data science career.
A method to find a statistical relationship between two variables in a dataset where one variable is used to group data.
Seaborn library has matplotlib at its core for data point visualizations. This library gives highly statistical informative graphics functionality to Seaborn.
The Matplotlib library helps you create static and dynamic visualisations. Dynamic visualizations that are animated and interactive. This library makes it easy to plot data and create graphs.
This library is named Plotly after the company of the same name. Plotly provides visualization libraries for Python, R, MATLAB, Perl, Julia, Arduino, and REST.
Numpy array have functions for matrices ,linear algebra ,Fourier Transform. Numpy arrays provide 50x more speed than a python list.
Numpy has created a vast ecosystem spanning numerous fields of science.
Pandas is a easy to use data analysis and manipulation tool. Pandas provides functionality for categorical,ordinal, and time series data . Panda provides fast and powerful calculations for data analysis.
In this tutorial, you will learn How to Access The Data in Various Ways From the dataframe.
Understand one of the important data types in Python. Each item in a set is distinct. Sets can store multiple items of various types of data.
Tuples are a sequence of Python objects. A tuple is created by separating items with a comma. They are put inside the parenthesis “”(“” , “”)””.
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