Mastering Data Science With Python [2023] Online Course

Mastering Data Science with Python [2023]

All levels
English

Course Description

Unlock the Power of Python for Data Science and Visualization Welcome to a comprehensive Python programming course tailored by Selfcode Academy for data science and visualization enthusiasts. Whether you're a beginner or looking to expand your skill set, this course will equip you with the knowledge you need. Master the Python Basics: Start from scratch with Python fundamentals. Learn about variables, data types, and the logic behind programming. Explore conditional statements and loops. Dive into essential data structures like lists, tuples, dictionaries, and sets. Discover the world of functions, including powerful lambda functions. Get familiar with Object-Oriented Programming (OOP) concepts. Python's Role in Data Science: Transition to data science seamlessly. Manipulate dates and times using Python's datetime module. Tackle complex text patterns with regular expressions (regex). Harness the power of built-in Python functions. Embrace NumPy for efficient numerical computing. Master Pandas and its data structures, including Series and DataFrames. Acquire data cleaning skills to handle missing values and outliers. Excel at data manipulation with Pandas, including indexing, grouping, sorting, and merging. Dive into data visualization with Matplotlib to create compelling graphs. Advanced Data Science and Visualization: Uncover insights through Exploratory Data Analysis (EDA) techniques. Automate data analysis with Pandas Profiling, DABL, and Sweetviz. Perfect your data cleaning and preprocessing techniques. Craft captivating visualizations using Seaborn. Create various plots, from lines and areas to scatter and violin plots with Plotly. Take your data to the map with geographical visualizations. Statistics and Hypothesis Testing: Dive into descriptive statistics, including central tendency and dispersion. Master inferential statistics, covering sampling, confidence intervals, and hypothesis testing. Learn to conduct hypothesis tests using Python libraries. Capstone Project: Apply your skills to a real-world data science project. Define a business problem and structure your analysis. Summarize your findings in a comprehensive report. Upon completing this course, you'll have a strong foundation in Python programming for data science and visualization. You'll possess the expertise to clean, analyze, and visualize data, empowering you to make data-driven decisions confidently. Don't miss this opportunity to embark on your data science journey. Enroll now and unleash the potential of Python for data exploration and visualization!

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What you’ll learn

Master the Python Basics (Video Lecture)
Python's Role in Data Science (Video Lecture)
Advanced Data Science and Visualization (Video Lecture)
Statistics and Hypothesis Testing (Video Lecture)
Capstone Project (Video Lecture)
Practice Sheet (PDF)

Covering Topics

Module 1: Master the Python Basics

Module 2: Python's Role in Data Science

Module 3: Advanced Data Science and Visualization

Module 4: Statistics and Hypothesis Testing

Module 5: Capstone Project

Curriculum

Our Python Data Science and Visualization course is designed to empower students with a strong foundation in Python programming while seamlessly transitioning them into the exciting field of data science. Beginning with Python fundamentals, students learn essential concepts like variables, data types, loops, and functions, making it accessible even to beginners. As they progress, they acquire hands-on experience through coding exercises and practical projects, ensuring they can apply their knowledge to real-world scenarios confidently.

The curriculum also introduces vital data science libraries such as NumPy and Pandas, enabling students to efficiently manipulate and analyze data, a skill highly sought after in the data science domain. Data visualization is a key focus, with comprehensive coverage of Matplotlib, Seaborn, and Plotly to create diverse and compelling visualizations.

Beyond the basics, students explore advanced techniques like exploratory data analysis (EDA) and geographical visualizations, expanding their skill set. They also gain a solid understanding of both descriptive and inferential statistics, learning to conduct hypothesis tests using Python libraries.

A unique feature of our course is the Capstone Project, where students apply their acquired skills to a real-world data science project. This practical experience not only enhances their portfolio but also prepares them for data-related career opportunities. Whether you're a beginner or seeking to advance your data science journey, this course equips you with the tools and knowledge needed to succeed in the data-driven world.

Frequently Asked Questions

This course is designed for both beginners and individuals looking to expand their skills in Python programming for data science and visualization. It's suitable for anyone interested in data analysis, data visualization, or those transitioning into data science from other fields.

No, you don't need prior programming experience. This course starts from scratch with Python fundamentals and gradually builds up your skills. However, having a basic understanding of mathematics and statistics can be helpful.

In the Python basics section, you'll learn about variables, data types, conditional statements, loops, data structures like lists, tuples, dictionaries, and sets. You'll also explore functions, including lambda functions, and get familiar with Object-Oriented Programming (OOP) concepts.

Python is a widely used programming language in the field of data science. In this course, you will learn how to use Python for data manipulation, data cleaning, and data visualization. Python libraries like NumPy and Pandas are introduced for efficient data handling.

Yes, hands-on practice is a key component of this course. You'll work on coding exercises and projects throughout the course to apply what you've learned. The Capstone Project at the end allows you to work on a real-world data science project.

Yes, this course covers data visualization using Matplotlib, Seaborn, and Plotly. You'll learn how to create a wide range of graphs and visualizations to effectively communicate your findings.

The course duration may vary depending on your learning pace. On average, it may take several weeks to complete all the modules and the Capstone Project. You can learn at your own pace and revisit the material as needed.