Python for Data Science: Python Programming & Data Analysis

Python for Data Science: Python Programming & Data Analysis, available at $54.99, has an average rating of 4.27, with 41 lectures, 19 quizzes, based on 27 reviews, and has 3102 subscribers.

You will learn about Gain a thorough understanding of Python syntax, script writing, and fundamental programming concepts such as variables, data types, and string operations Become adept at using lists, dictionaries, tuples, and sets for organizing and managing data effectively within Python Master the use of conditional statements and loops in Python to automate and optimize data processing tasks Learn to design reusable Python functions to perform repetitive tasks efficiently, including knowledge of recursion and lambda functions Acquire skills in reading from and writing to files in Python, crucial for data processing tasks in real-world applications Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format for analysis Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python This course is ideal for individuals who are Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling. or Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis. or Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning. or Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities. It is particularly useful for Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling. or Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis. or Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning. or Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities.

Enroll now: Python for Data Science: Python Programming & Data Analysis

Summary

Title: Python for Data Science: Python Programming & Data Analysis

Price: $54.99

Average Rating: 4.27

Number of Lectures: 41

Number of Quizzes: 19

Number of Published Lectures: 41

Number of Published Quizzes: 19

Number of Curriculum Items: 69

Number of Published Curriculum Objects: 69

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

• Gain a thorough understanding of Python syntax, script writing, and fundamental programming concepts such as variables, data types, and string operations
• Become adept at using lists, dictionaries, tuples, and sets for organizing and managing data effectively within Python
• Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
• Learn to design reusable Python functions to perform repetitive tasks efficiently, including knowledge of recursion and lambda functions
• Acquire skills in reading from and writing to files in Python, crucial for data processing tasks in real-world applications
• Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
• Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format for analysis
• Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python

Who Should Attend

• Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling.
• Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis.
• Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning.
• Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities.

Target Audiences

• Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling.
• Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis.
• Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning.
• Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities.