Course Overview

Students will gain an introduction to statistics in this course, covering topics such as data sources, research design, data administration, and data exploration and visualisation. The ability to recognise various data kinds as well as analyse, visualise, and comprehend summaries of both univariate and multivariate data will be taught to learners.

Along with these concepts, learners will also learn about sample estimates' variability, the distinctions between probability and non-probability sampling from bigger populations, and how probability sampling can be used to draw conclusions about larger populations.

Students will use Python in the course environment to apply the statistical ideas they have studied at the end of each week. Learners will discover the various applications of Python as a tool, including the Numpy, Statsmodels, Pandas, Matplotlib, and Seaborn libraries, during these lab-based lessons. There are tutorial films available to guide learners through the Python processes of managing data and creating visualisations. The Jupyter Notebook environment available on Coursera is used in this course.

What you'll learn

• ?Statistics
• ?Data Analysis
• ?Python Programming
• ?Python Programming

Requirements

• ?Basic knowledge of Understanding and Visualizing Data with Python.
• ?A computer or laptop with internet connectivity.
• ?Learn about Understanding and Visualizing Data with Python in nineteen hours.
• Flexible work schedule.

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Enhanced Employability:

An outstanding Understanding and Visualizing Data with Python Certificate that increases your chances of landing the best jobs.

Competitive Advantage:

An opportunity to stand out from the competition and make a more significant impression on potential employers.

Skill Validation:

Robust validation of your Understanding and Visualizing Data with Python skills confirms that you can complete all related tasks.

Networking Opportunities:

The Understanding and Visualizing Data with Python Certificate course provides ample networking opportunities for participants. Learners can connect with classmates and industry professionals through cooperative exercises, group discussions, and interactive seminars.