Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
19 Hour(s) 31 Minute(s)
Language
English
Taught by
Selfcode Academy
Rating
Course Overview
Master data analysis using Python, pandas, NumPy, data visualization, and real-world projects.
In this comprehensive course, "Data Analysis with Python," you will embark on a journey to become a proficient data analyst equipped with the essential skills and tools needed to analyze, visualize, and interpret data effectively. This course is designed for beginners and professionals alike, providing a solid foundation in data analysis using Python.
Throughout the course, you will:
Learn the fundamentals of Python programming and its application in data analysis.
Explore key libraries such as pandas and NumPy for data manipulation and analysis.
Gain expertise in data cleaning, preprocessing, and handling missing values.
Develop skills in exploratory data analysis (EDA) and create insightful visualizations using Matplotlib and Seaborn.
Understand the principles of file handling and data importing from various sources including CSV, JSON, and Excel.
Apply advanced techniques such as object-oriented programming (OOP) and work on real-world data analysis projects.
Learn to gather data from APIs, perform linear algebra operations with NumPy, and execute a comprehensive capstone project.
By the end of this course, you will have the confidence and skills to tackle complex data analysis tasks, making you a valuable asset in any data-driven organization.
Whether you are an aspiring data analyst, a professional looking to enhance your data skills, or a student interested in data science, this course will provide you with the knowledge and hands-on experience needed to excel in the field of data analysis.
Course Content
- 10 section(s)
- 47 lecture(s)
- Section 1 Introduction to Business and Data
- Section 2 Python Basics and Jupyter Notebooks
- Section 3 Basic Python Syntax
- Section 4 Functions and Sequences
- Section 5 Object-Oriented Programming (OOP) and NumPy
- Section 6 Pandas Library and Data Manipulation
- Section 7 Working with Files and Data Importing
- Section 8 Data Cleaning and Preprocessing
- Section 9 Exploratory Data Analysis (EDA)
- Section 10 Advanced Topics
What You’ll Learn
- Students will learn to analyze business data using Python and essential libraries like pandas and NumPy.
- Students will visualize data effectively with popular Python libraries such as Matplotlib and Seaborn.
- Students will perform data cleaning, preprocessing, and exploratory data analysis (EDA).
- Students will execute real-world data analysis projects, including data gathering and API utilization.
Skills covered in this course
Reviews
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SShreshth Vijayvargiya
help a lot
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ssatish
I reviewed the course twice to make sure I understood everything. The course was beneficial
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ggeorge
This is an excellent course.
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SShazia Manzoor
It is hard to understand the accent and there's no fluency in the language. There's also too much use of "correct". I realized these problems after making the purchase.
