Build Practical Programming Skills
Laern Data Analysis
Data Analysis and Machine Learning with Python
Instructor
kehinde solomon o ogunsanya
Course Overview
Build practical software skills through hands-on, project-based learning you can put to use right away.
Welcome to our course, "Data Analysis with Python Pandas and Machine Learning Model"!
This course is designed to provide you with a comprehensive understanding of the powerful data analysis and manipulation capabilities of the Pandas library in Python, as well as the fundamental concepts and techniques of linear regression, one of the most widely used machine learning models.
You will learn how to use the Pandas library to prepare, clean, and analyze data, as well as how to use machine learning models such as linear regression to make predictions and interpret data insights. The course places a strong emphasis on data cleaning and preparation, which is a critical step in the data analysis process and is often overlooked in other courses.
Throughout the course, you will gain hands-on experience with data cleaning, preparation, and visualization techniques, including handling missing values, working with categorical data, and reshaping and pivoting data. You will also learn how to use various visualization and statistical techniques to understand the structure and characteristics of your data through Exploratory Data Analysis (EDA).
You will learn how to implement linear regression model in Pandas and Scikit-learn, evaluate their performance using various metrics, and interpret model coefficients and their significance.
This course is suitable for different levels of audiences, from beginner to advanced, who are interested in data analysis and machine learning. The course provides a hands-on approach to learning, with real-world examples that allow learners to apply the concepts and techniques they've learned.
By the end of the course, you will have a solid understanding of the data analysis and manipulation capabilities of Pandas and the concepts and techniques of linear regression, as well as the ability to analyze, report, and interpret data using a machine learning model.
Join us now and take your data analysis and machine learning skills to the next level!
Who this course is for:
- Students and recent graduates who are interested in data analysis and machine learning and want to learn how to use Python and Pandas for these tasks
- Software developers who want to add data analysis and machine learning capabilities to their skillset
- Any one who wants to gain in-depth understanding of data cleaning, preparation, visualization, data analysis and machine learning models
Learn at your own pace Work through the course content in a structured learning environment and track your progress as you move forward.
Why Take This Course?
- Build practical development skills through hands-on learning.
- Understand tools and workflows used to create real software.
- Develop projects that demonstrate your technical ability.
- Strengthen your problem-solving and debugging skills.
Who This Course Is For
Designed for learners who are new to programming and want to build practical development skills from the ground up. The course focuses on hands-on coding and real project work, so you finish with skills you can put to use straight away -- whether that means building your own applications or contributing confidently to a development team. Along the way, you'll work through topics such as Introduction to Pandas and Data Visualization with Matplotlib Seaborn and Plotly.
Requirements
- No prior programming experience is required. A computer and a willingness to practice are recommended.
- A device with internet access to view the course content.
Complete the required course activities to earn your Roladel Learn certificate of completion.
Curriculum
Follow the course step by step, from core concepts to writing, testing and shipping real code.
- Indexing and slicing of Series and DataFrame
- Filtering, sorting, and aggregating data
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removing duplicate data
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Data encoding and normalization in pandas
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Merging and joining DataFrames
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Handling Dates and Times
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GroupBy operations
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Pivot table in Pandas
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Reading and writing data from various file formats (e.g. CSV, Excel, JSON)
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Calculating summary statistics
Programming
Where You Can Apply These Skills
The skills covered in this course can be applied to freelance projects, personal websites, client work, software projects and further development learning.
