US$138
weeklyor US$275 for 8 classes
包含什麼
8 現場會議
8 上課時間作業
每週 2-4 小時. 7或以上 整堂課項目
7或以上 整堂課完成證書
1堂 課程結束後我們無法翻譯此文,請刷新頁面並再試一次。
課堂經歷
英語程度 - B2+
美國 7 - 10 年級
Beginner 等級
Data is everywhere—from financial markets to healthcare research to space exploration. In today’s world, the ability to analyze and interpret data is a highly valuable skill that opens doors to careers in STEM, business, and technology. This 8-week hands-on course introduces high school students to data science and analytics using Python, helping them build critical thinking, problem-solving, and data literacy skills. Using real-world datasets from finance, health sciences, and space exploration, students will learn how to clean, analyze, and visualize data using industry-standard tools like pandas, numpy, and matplotlib in Google Colab. Each week, they will apply new skills to explore financial trends, track health statistics, and analyze NASA mission data. With step-by-step guidance, students will develop confidence in handling large datasets, identifying patterns, and making data-driven decisions. By the end of the course, students will complete a mini-project, showcasing their ability to analyze and present real-world data—an excellent addition to their academic portfolio, STEM competitions, or college applications. Whether your learner is interested in computer science, engineering, finance, or research, this course will provide a strong foundation in data science, setting them up for success in higher education and beyond! Course Highlights ✔ Hands-on learning with real-world datasets from finance, health sciences, and space exploration ✔ Python programming using pandas, numpy, and matplotlib in Google Colab ✔ Step-by-step guidance on data cleaning, analysis, and visualization ✔ Introduction to key data science concepts like statistics, time-series analysis, and regression ✔ Weekly coding exercises & practice problems to reinforce learning ✔ No additional software needed—everything runs in the cloud with Google Colab ✔ Final project opportunity to apply skills and showcase learning ✔ Valuable STEM skills for future careers in data science, finance, healthcare, and technology ****Important Note for Adults***** This isn't a beginner coding course. Learners should already be comfortable with basic programming concepts in any language (Python, Java, JavaScript, C/C++, or Swift). If you're new to coding, check out our beginner Python courses first - they'll give you the foundation you need to succeed here.
學習目標
Load, clean, and manipulate real-world datasets using pandas and numpy.
Students will learn how to import, inspect, and clean datasets using Python’s pandas and numpy libraries, ensuring their data is structured and ready for analysis.
Use visualization tools (matplotlib, seaborn) to interpret data.
Students will create graphs, charts, and heat-maps to visualize trends and patterns, making their data-driven insights easier to understand.
教學大綱
8 課程
超過 2 週課 1:
Introduction to Data Science & Google Colab
Welcome to data science! In this session, students will get an overview of the data science workflow, including data collection, cleaning, analysis, and visualization. They will set up Google Colab, learn the basics of working with pandas and numpy, and explore a sample dataset to understand different data types and structures.
60 分鐘線上直播課
課 2:
Data Cleaning & Preprocessing (Finance Dataset)
Before analyzing data, we need to clean it! This week, students will learn how to handle missing data, remove duplicates, and fix formatting issues using pandas. We will explore a financial dataset, such as stock prices or cryptocurrency trends, and practice preparing messy data for analysis.
60 分鐘線上直播課
課 3:
Data Manipulation & Descriptive Statistics (Health Dataset)
How do we summarize and extract insights from large datasets? Students will learn how to use pandas for filtering, sorting, and grouping data while exploring key statistical measures like mean, median, and standard deviation. Using a health sciences dataset (e.g., heart disease or nutrition data), they will practice applying data manipulation techniques
60 分鐘線上直播課
課 4:
Data Visualization & Trends (Finance & Health Data)
A picture is worth a thousand rows of data! This session introduces matplotlib and seaborn for creating line graphs, bar charts, and scatter plots. Students will visualize financial and health trends, learning how to communicate insights effectively through graphs. They will also explore best practices for choosing the right visualization for different data types
60 分鐘線上直播課
其他詳情
父母的引導和規範
Learners will use Google Colab during this class and will need a Google Account to access Colab. Students will also utilize the following Python libraries, including NumPy, Matplotlib, Seaborn, and Pandas throughout the class. The documentation (instructions) for these libraries will be used as a reference throughout the course. UC Irvine ML Repository and Kaggle datasets will be used for practice datasets throughout the class. Python.org will be used as Python reference sources throughout the class.
先決條件
This isn't a beginner coding course. Learners should already be comfortable with basic programming concepts in any language (Python, Java, JavaScript, C/C++, or Swift). If you're new to coding, check out our beginner Python courses first.
外部資源
除了 Outschool 教室外,本課程也使用:
認識老師
教師專業知識和證書
學士學位 由 Mount St. Mary's University
Over 5,000 students from nearly 130 countries across a variety of platforms have started coding in one of my classes. I offer classes covering the foundations of Python and AI. I am an Outschool Ace Educator with over 800 5 star reviews and personally teach every class. Before teaching, I worked as a software developer for nearly 10 years. I've worked for organizations including Apple, Dell, and Best Buy. I believe the best way to learn is by doing and all my classes are based around hands-on projects that progressively build in difficulty. I'm a graduate of Mount St. Mary's University in Emmitsburg, Maryland. I can't wait to meet your learner in the class and get started soon.
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