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The language used throughout the course, in both instruction and assessments.
The language used throughout the course, in both instruction and assessments.
Statistics with Python refers to the application of Python programming language in statistics. Python is a versatile language with many libraries and modules like NumPy, SciPy, pandas, Matplotlib, and Seaborn, specifically designed for statistical analysis and data visualization. By learning Statistics with Python, you can perform complex statistical tests, data analysis, data manipulation, and visualization, essential skills for data scientists and analysts. Python's simplicity and readability also make it a popular choice for beginners in statistics and programming.‎
Data Scientist: They use Python for data analysis, predictive modeling, and statistical testing.
Machine Learning Engineer: They use Python to develop algorithms to learn from and make predictions based on data.
Quantitative Analyst: They use Python for statistical analysis in the finance industry, often to predict market trends.
Business Analyst: They use Python to analyze business data and provide insights to management.
Bioinformatics Specialist: They use Python for statistical analysis in biological and medical research.
Market Research Analyst: They use Python to analyze market data and predict consumer behavior.
Data Journalist: They use Python to analyze and visualize data for storytelling.
Risk Analyst: They use Python to analyze business financial risks.
Sports Analyst: They use Python to analyze player performance and team strategies.
To start learning Statistics with Python on Coursera: