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BEGIN:VEVENT
DTSTART:20260407T190000Z
DTEND:20260407T203000Z
DTSTAMP:20260407T000000Z
SUMMARY:Python Coding Essentials for Data Science
DESCRIPTION:This four-part workshop introduces the core Python skills 
 needed for data science — from loading raw data to building a basic 
 machine learning model.\n\nYou will learn how to clean\, explore\, 
 visualize\, and analyze data using Python. By the end of the workshop\, you 
 will understand the complete workflow: data preprocessing → exploratory 
 analysis → model building → evaluation.\n\nMany people use AI tools to 
 generate Python code. In this workshop\, you will learn the fundamentals 
 behind that code so you can understand it\, check for errors\, and use it 
 confidently.\n\nThe workshop meets once a week on Tuesdays for four weeks. 
 No prior Python experience is required. Participation is free\, but 
 registration is required.\n\nWe will use Google Colab\, a free cloud-based 
 platform for Python coding. If you are new to Colab\, I recommend attending 
 the introductory workshop first: 
 https://calendar.lib.olemiss.edu/event/16040287\n\nWeekly Topics\n\nWeek 1: 
 Getting Started with Python\n\n\n	\n	Load data\n	\n	\n	Inspect and 
 summarize data\n	\n	\n	Create simple visualizations\n	\n\n\nWeek 2: Data 
 Cleaning & Preparation\n\n\n	\n	Handle missing values\n	\n	\n	Filter and 
 rename data\n	\n	\n	Create new features\n	\n	\n	Detect 
 outliers\n	\n\n\nWeek 3: Exploring the Data (EDA)\n\n\n	\n	Descriptive 
 statistics\n	\n	\n	Grouping and aggregation\n	\n	\n	Visual 
 exploration\n	\n	\n	Interpreting results\n	\n\n\nWeek 4: Introduction to 
 Machine Learning\n\n\n	\n	Split data into training and test 
 sets\n	\n	\n	Train a simple model\n	\n	\n	Evaluate 
 performance\n	\n	\n	Understand feature importance\n	\n	\n	k-fold 
 cross-validation\n	\n\n\nContact\n\nFor questions\, please contact:\nDr. 
 Sian Lee\nslee63@olemiss.edu\n
LOCATION:Classroom 106 D
ORGANIZER;CN="Cody Ray":MAILTO:wcray@olemiss.edu
CATEGORIES:Workshop
CONTACT;CN="Cody Ray":MAILTO:wcray@olemiss.edu
STATUS:CONFIRMED
UID:LibCal-16040348
URL:https://calendar.lib.olemiss.edu/event/16040348
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TRIGGER:-PT15M
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DESCRIPTION:Reminder
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BEGIN:VEVENT
DTSTART:20260414T190000Z
DTEND:20260414T203000Z
DTSTAMP:20260414T000000Z
SUMMARY:Python Coding Essentials for Data Science
DESCRIPTION:This four-part workshop introduces the core Python skills 
 needed for data science — from loading raw data to building a basic 
 machine learning model.\n\nYou will learn how to clean\, explore\, 
 visualize\, and analyze data using Python. By the end of the workshop\, you 
 will understand the complete workflow: data preprocessing → exploratory 
 analysis → model building → evaluation.\n\nMany people use AI tools to 
 generate Python code. In this workshop\, you will learn the fundamentals 
 behind that code so you can understand it\, check for errors\, and use it 
 confidently.\n\nThe workshop meets once a week on Tuesdays for four weeks. 
 No prior Python experience is required. Participation is free\, but 
 registration is required.\n\nWe will use Google Colab\, a free cloud-based 
 platform for Python coding. If you are new to Colab\, I recommend attending 
 the introductory workshop first: 
 https://calendar.lib.olemiss.edu/event/16040287\n\nWeekly Topics\n\nWeek 1: 
 Getting Started with Python\n\n\n	\n	Load data\n	\n	\n	Inspect and 
 summarize data\n	\n	\n	Create simple visualizations\n	\n\n\nWeek 2: Data 
 Cleaning & Preparation\n\n\n	\n	Handle missing values\n	\n	\n	Filter and 
 rename data\n	\n	\n	Create new features\n	\n	\n	Detect 
 outliers\n	\n\n\nWeek 3: Exploring the Data (EDA)\n\n\n	\n	Descriptive 
 statistics\n	\n	\n	Grouping and aggregation\n	\n	\n	Visual 
 exploration\n	\n	\n	Interpreting results\n	\n\n\nWeek 4: Introduction to 
 Machine Learning\n\n\n	\n	Split data into training and test 
 sets\n	\n	\n	Train a simple model\n	\n	\n	Evaluate 
 performance\n	\n	\n	Understand feature importance\n	\n	\n	k-fold 
 cross-validation\n	\n\n\nContact\n\nFor questions\, please contact:\nDr. 
 Sian Lee\nslee63@olemiss.edu\n
LOCATION:Classroom 106 D
ORGANIZER;CN="Cody Ray":MAILTO:wcray@olemiss.edu
CATEGORIES:Workshop
CONTACT;CN="Cody Ray":MAILTO:wcray@olemiss.edu
STATUS:CONFIRMED
UID:LibCal-16040349
URL:https://calendar.lib.olemiss.edu/event/16040349
X-MICROSOFT-CDO-BUSYSTATUS:BUSY
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ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
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BEGIN:VEVENT
DTSTART:20260421T190000Z
DTEND:20260421T203000Z
DTSTAMP:20260421T000000Z
SUMMARY:Python Coding Essentials for Data Science
DESCRIPTION:This four-part workshop introduces the core Python skills 
 needed for data science — from loading raw data to building a basic 
 machine learning model.\n\nYou will learn how to clean\, explore\, 
 visualize\, and analyze data using Python. By the end of the workshop\, you 
 will understand the complete workflow: data preprocessing → exploratory 
 analysis → model building → evaluation.\n\nMany people use AI tools to 
 generate Python code. In this workshop\, you will learn the fundamentals 
 behind that code so you can understand it\, check for errors\, and use it 
 confidently.\n\nThe workshop meets once a week on Tuesdays for four weeks. 
 No prior Python experience is required. Participation is free\, but 
 registration is required.\n\nWe will use Google Colab\, a free cloud-based 
 platform for Python coding. If you are new to Colab\, I recommend attending 
 the introductory workshop first: 
 https://calendar.lib.olemiss.edu/event/16040287\n\nWeekly Topics\n\nWeek 1: 
 Getting Started with Python\n\n\n	\n	Load data\n	\n	\n	Inspect and 
 summarize data\n	\n	\n	Create simple visualizations\n	\n\n\nWeek 2: Data 
 Cleaning & Preparation\n\n\n	\n	Handle missing values\n	\n	\n	Filter and 
 rename data\n	\n	\n	Create new features\n	\n	\n	Detect 
 outliers\n	\n\n\nWeek 3: Exploring the Data (EDA)\n\n\n	\n	Descriptive 
 statistics\n	\n	\n	Grouping and aggregation\n	\n	\n	Visual 
 exploration\n	\n	\n	Interpreting results\n	\n\n\nWeek 4: Introduction to 
 Machine Learning\n\n\n	\n	Split data into training and test 
 sets\n	\n	\n	Train a simple model\n	\n	\n	Evaluate 
 performance\n	\n	\n	Understand feature importance\n	\n	\n	k-fold 
 cross-validation\n	\n\n\nContact\n\nFor questions\, please contact:\nDr. 
 Sian Lee\nslee63@olemiss.edu\n
LOCATION:Classroom 106 D
ORGANIZER;CN="Cody Ray":MAILTO:wcray@olemiss.edu
CATEGORIES:Workshop
CONTACT;CN="Cody Ray":MAILTO:wcray@olemiss.edu
STATUS:CONFIRMED
UID:LibCal-16040350
URL:https://calendar.lib.olemiss.edu/event/16040350
X-MICROSOFT-CDO-BUSYSTATUS:BUSY
BEGIN:VALARM
TRIGGER:-PT15M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
DTSTART:20260428T190000Z
DTEND:20260428T203000Z
DTSTAMP:20260428T000000Z
SUMMARY:Python Coding Essentials for Data Science
DESCRIPTION:This four-part workshop introduces the core Python skills 
 needed for data science — from loading raw data to building a basic 
 machine learning model.\n\nYou will learn how to clean\, explore\, 
 visualize\, and analyze data using Python. By the end of the workshop\, you 
 will understand the complete workflow: data preprocessing → exploratory 
 analysis → model building → evaluation.\n\nMany people use AI tools to 
 generate Python code. In this workshop\, you will learn the fundamentals 
 behind that code so you can understand it\, check for errors\, and use it 
 confidently.\n\nThe workshop meets once a week on Tuesdays for four weeks. 
 No prior Python experience is required. Participation is free\, but 
 registration is required.\n\nWe will use Google Colab\, a free cloud-based 
 platform for Python coding. If you are new to Colab\, I recommend attending 
 the introductory workshop first: 
 https://calendar.lib.olemiss.edu/event/16040287\n\nWeekly Topics\n\nWeek 1: 
 Getting Started with Python\n\n\n	\n	Load data\n	\n	\n	Inspect and 
 summarize data\n	\n	\n	Create simple visualizations\n	\n\n\nWeek 2: Data 
 Cleaning & Preparation\n\n\n	\n	Handle missing values\n	\n	\n	Filter and 
 rename data\n	\n	\n	Create new features\n	\n	\n	Detect 
 outliers\n	\n\n\nWeek 3: Exploring the Data (EDA)\n\n\n	\n	Descriptive 
 statistics\n	\n	\n	Grouping and aggregation\n	\n	\n	Visual 
 exploration\n	\n	\n	Interpreting results\n	\n\n\nWeek 4: Introduction to 
 Machine Learning\n\n\n	\n	Split data into training and test 
 sets\n	\n	\n	Train a simple model\n	\n	\n	Evaluate 
 performance\n	\n	\n	Understand feature importance\n	\n	\n	k-fold 
 cross-validation\n	\n\n\nContact\n\nFor questions\, please contact:\nDr. 
 Sian Lee\nslee63@olemiss.edu\n
LOCATION:Classroom 106 D
ORGANIZER;CN="Cody Ray":MAILTO:wcray@olemiss.edu
CATEGORIES:Workshop
CONTACT;CN="Cody Ray":MAILTO:wcray@olemiss.edu
STATUS:CONFIRMED
UID:LibCal-16040351
URL:https://calendar.lib.olemiss.edu/event/16040351
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