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One way to make a difference is by practicing kindness in your daily interactions with others. This could be as simple as holding the door open for someone, offering a smile or compliment, or lending a listening ear to a friend or stranger. Small acts of kindness can have a ripple effect and contribute to a more positive and compassionate world.

How to help the environment

To help the environment, there are many things we can do in our daily lives. One of the most important is to reduce our waste by using reusable bags, containers, and water bottles, and recycling whenever possible.

Volunteer opportunities

One of the most popular volunteer opportunities is in environmental organizations, where volunteers can help with tasks such as cleaning up litter, planting trees, and conducting environmental research.

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Summarize Wikipedia Python

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What is the latest version of Python?

The latest version of Python is Python 3.10.0 as of September 2021.

What is a tuple in Python?

A tuple in Python is a collection of ordered, immutable elements that can include various data types, such as integers, strings, and even other tuples

What are the main data types in Python?

The main data types in Python include numeric, boolean, string, list, tuple, set, and dictionary.

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Python for Data Science, AI & Development

Python for Data Science

Eliott Hanson

Offered By

Enroll

$120

English

Certificate

2 Months

9th Jan, 2023

Beginner

Arabic, French, Portuguese, Italian, German, Russian, English, Spanish, Korean, Japanese

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About

Instructors

Syllabus

Reviews

FAQ

About this Course

This course covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in Python, and conducting reproducible research.

Show all

The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. This specialization is presented for learners who want to start and complete the foundational part of the curriculum first, before moving onto the more advanced topics in Data Science: Statistics and Machine Learning.

WHAT YOU WILL LEARN

Use Python to clean, analyze and visualize data.

Use GitHub to manage data science projects.

Learn how to ask the right questions, obtain data,

Set up Python, Github and other useful tools

SKILLS YOU WILL GAIN

Python

Machine Learning

GitHub

Exploratory Data Analysis

Instructors

Eliott Hanson, Phd

Computer Science Professor

School of Computer Science

Jean Long

Computer Science Professor

School of Computer Science

Syllabus

Introduction

Welcome to Introduction to Data Science with Python!

Syllabus Quiz (8 Questions)

Important Pre-Course Survey

Section 1: Linear Regression

Pre-reading

1.1 Introduction to Regression

1.2 Error Evaluation and Model Comparison

1.3 Linear Regression

Section 2: Multiple and Polynomial Regression

Pre-reading

2.1 Multiple Regression

2.2 Techniques for Multilinear Modeling

2.3 Polynomial Regression

Section 3: Model Selection and Cross-Validation

Pre-reading

3.1 Model Selection

3.2 Cross-Validation

Section 4: Bias, Variance, and Hyperparameters

Pre-reading

4.1 Introductory Exercise

4.2 Bias and Variance

4.3 Ridge and LASSO

Section 5: Classification and Logistic Regression

Pre-reading

5.1 Classification and kNN

5.2 Logistic Regression

Section 6: Multi-logstic Regression and Missingness

Pre-reading

6.1 Multinomial Logistic Regression

6.2 Missingness

Section 7: Bootstrap, Confidence Intervals, and Hypothesis Testing

Pre-reading

7.1 Inference in Linear Regression

7.2 Bootstrap and Confidence Intervals

7.3 Evaluating Predictor Significance

Section 8: Capstone Project

No Pre-reading

8.1 Introduction

8.2 Why is accuracy not enough?

8.3 Bayes Threshold

Wrap-up

Important post-course surveys

Review Videos

Week 3

Final Notes

Reviews

Inez Sierra

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Inez Sierra

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Emir O'Sullivan

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Frequently Asked Questions

When will I have access to the lectures and assignments?

Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

What are the requirements to attend this course?

Access to a computer with an internet connection.

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COURSE

Python for Data Science, AI & Development

IBM

COURSE

Python for Data Science, AI & Development

IBM

PDF

URL

DOCX

TXT

Audio

Video

YouTube

GitHub

Course

From URL

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Add Resource

Train Mentor with Resource

COURSE

Python for Data Science, AI & Development

IBM

PATHWAY

Machine Learning Foundations

Google

VIDEO

Introduction to Artificial Intelligence

Stanford University

COURSE

Advanced Python for Machine Learning

Google

PATHWAY

Data Visualization with Javascript

IBM

Document

Jupyter notebooks

IBM

Machine learning is the science of getting computers to act without being explicitly programmed.

Introductory

20 Minutes

0.28 pts

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Python for Beginners

Eliott Hanson

Offered By

Enroll

20 Minutes

View this Video

About this Video

This video covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in Python, and conducting reproducible research.

Show all

Instructors

Eliott Hanson, Phd

Computer Science Professor

School of Computer Science

Jean Long

Computer Science Professor

School of Computer Science

Syllabus

Introduction

Welcome to Introduction to Data Science with Python!

Syllabus Quiz (8 Questions)

Important Pre-Course Survey

Section 1: Linear Regression

Pre-reading

1.1 Introduction to Regression

1.2 Error Evaluation and Model Comparison

1.3 Linear Regression

Section 2: Multiple and Polynomial Regression

Pre-reading

2.1 Multiple Regression

2.2 Techniques for Multilinear Modeling

2.3 Polynomial Regression

Section 3: Model Selection and Cross-Validation

Pre-reading

3.1 Model Selection

3.2 Cross-Validation

Section 4: Bias, Variance, and Hyperparameters

Pre-reading

4.1 Introductory Exercise

4.2 Bias and Variance

4.3 Ridge and LASSO

Section 5: Classification and Logistic Regression

Pre-reading

5.1 Classification and kNN

5.2 Logistic Regression

Section 6: Multi-logstic Regression and Missingness

Pre-reading

6.1 Multinomial Logistic Regression

6.2 Missingness

Section 7: Bootstrap, Confidence Intervals, and Hypothesis Testing

Pre-reading

7.1 Inference in Linear Regression

7.2 Bootstrap and Confidence Intervals

7.3 Evaluating Predictor Significance

Section 8: Capstone Project

No Pre-reading

8.1 Introduction

8.2 Why is accuracy not enough?

8.3 Bayes Threshold

Wrap-up

Important post-course surveys

Review Videos

Week 3

Final Notes

Reviews

Inez Sierra

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Inez Sierra

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Emir O'Sullivan

"It has been an amazing journey. I learnt a lot from it and I will go through different topics especially, functions and OOPS to have a better understanding."

Frequently Asked Questions

When will I have access to the lectures and assignments?

What will I get if I subscribe to this Specialization?

What are the requirements to attend this course?

Access to a computer with an internet connection.

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