Python For Data Analysis and Data Science: Mastery with Pandas
Learn Python for Data Analysis and Data Science
Development,Data Science,Machine Learning
Lectures -102
Resources -6
Duration -15.5 hours
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Course Description
Python For Data Analysis and Data Science course will help you learn how to use Python for data science with Pandas, a powerful Python library for data manipulation and analysis. This course is designed for beginners and intermediates and covers all the basic and advanced features of Pandas.
Python For Data Analysis and Data Science: Mastery with Pandas Overview
This project-based course will teach you how to create and manipulate Pandas DataFrames, perform data cleaning and preprocessing, data aggregation and analysis, and data visualization. You will also learn about more advanced Pandas features, such as time series analysis and string manipulation.
You will also learn about more advanced Pandas features, such as time series analysis and string manipulation. If you are interested in learning how to use Python for data analysis and data science, then this course is for you.
Goals
What will you learn in this course:
- Create and manipulate Pandas DataFrames.
- Perform data cleaning and preprocessing.
- Perform data aggregation and analysis.
- Create data visualizations.
- Use advanced Pandas features, such as time series analysis and string manipulation.
Prerequisites
What are the prerequisites for this course?
- Basic knowledge of computers and programming is required.
- It is recommended that you download Anaconda, a free data science platform that includes Python and Pandas.
- Basic or intermediate experience with Microsoft Excel or other spreadsheet software is helpful but not required.
Curriculum
Check out the detailed breakdown of what’s inside the course
Getting Started
6 Lectures
- Course Introduction 03:35 03:35
- How To Get Most Out Of This Course 02:05 02:05
- How To Install Python IPython And Jupyter Notebook 08:26 08:26
- How To Install Anaconda For macOS And Linux Users 06:37 06:37
- How To Work With The Jupyter Notebook Part - 1 16:12 16:12
- How To Work With The Jupyter Notebook Part - 2 10:59 10:59
Pandas Building Blocks
2 Lectures
Pandas Data Structures
6 Lectures
Data Indexing And Selection
9 Lectures
Essential Functionalities
13 Lectures
Data Handling
8 Lectures
Data Cleaning And Preparation
17 Lectures
Data Wrangling
12 Lectures
Data Grouping And Aggregation
9 Lectures
Time Series Analysis
10 Lectures
How To Analyse With The Part of Real Life Projects
9 Lectures
Instructor Details
Pruthviraja L - Team UpGraduate
Software Trainer and Lead Instructor - Team UpGraduateHi, I am Pruthviraja L with the Software Training & Solutions Team "UpGraduate", with more than 9+ years of Training and Teaching experience from Technical Institutes, Teaching is my passion. I've obtained my both PG( M. Tech) in Power Systems Engineering and UG(B. E) in Electrical and Electronics Engineering from V. T. U - Belgaum, Karnataka, India.
Our Team is Proficient in visualizing data to execute projects & set rganizations on the path to profitability. 9+ years of teaching experience in engineering institutes with programming skills in Matlab, Python, SAS, R, Tableau, Git & GitHub, Linux OS, Data Analsys, Data Science, Machine Learning, Data Engineer and enthusiasm in developing AI and Machine learning skills motivated us to involve in the dynamic working environment to utilize skills and maximize the profit for the organization.
I'm a Certified Data Analyst. I got certifications from various eLearning centers including Udemy, Intellipaat-Bengaluru, LinkedIn eLearning center, Coursera-IBM, Tableau, etc.
I've successfully published and presented 6+ research papers in various 'National & International Journals and Conferences'. I'm a member of various National and International Journals including Elsevier and IEEE.
I'm a multi-faceted software professional aspirant with demonstrated capability in deploying analytical and programming methodologies to extract insights for boosting and bolstering user requirements. Adept at conducting statistical analysis and data modeling for transforming raw data into actionable strategies.
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