Numpy with Python

Numpy with Python, available at Free, has an average rating of 4.5, with 15 lectures, based on 213 reviews, and has 16196 subscribers.

You will learn about 1. NumPy Introduction 2. Python Numpy Array 3. Indexing & Slicing – 1 4. Indexing & Slicing – 2 5. Statistical Functions, Operators & Random Numbers 6. What is Data Science 7. What is Machine Learning This course is ideal for individuals who are Beginner Python developers curious about Data Science It is particularly useful for Beginner Python developers curious about Data Science.

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Summary

Title: Numpy with Python

Price: Free

Average Rating: 4.5

Number of Lectures: 15

Number of Published Lectures: 15

Number of Curriculum Items: 15

Number of Published Curriculum Objects: 15

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

1. NumPy Introduction 2. Python Numpy Array 3. Indexing & Slicing – 1 4. Indexing & Slicing – 2 5. Statistical Functions, Operators & Random Numbers 6. What is Data Science 7. What is Machine Learning

Who Should Attend

Beginner Python developers curious about Data Science

Target Audiences

Beginner Python developers curious about Data Science

In this series, we cover the basics of using NumPy for basic data analysis. Some of the things that are covered are as follows: installing NumPy using the Anaconda Python distribution, creating NumPy arrays in a variety of ways, gathering information about large datasets such as the mean, median and standard deviation, as well as utilizing Jupyter Notebooks for exploration using NumPy. If you are looking to get started with NumPy then join us!

1. NumPy Introduction

2. Python Numpy Array

3. Indexing & Slicing – 1

4. Indexing & Slicing – 2

5. Statistical Functions, Operators & Random Numbers

6. What is Data Science

7. What is Machine Learning

Course Curriculum

Chapter 1: Numpy with Python

Lecture 1: Session 1. NumPy Introduction

Lecture 2: NumPy Introduction

Lecture 3: Session 2. Python Numpy Array

Lecture 4: Python Numpy Array

Lecture 5: Session 3. Indexing & Slicing – 1

Lecture 6: Indexing & Slicing – 1

Lecture 7: Session 4. Indexing & Slicing – 2

Lecture 8: Indexing & Slicing – 2

Lecture 9: Session 5. Statistical Functions, Operators & Random Numbers

Lecture 10: Statistical Functions, Operators & Random Numbers

Lecture 11: Data Science

Lecture 12: 6. What is Data Science

Lecture 13: Machine Learning

Lecture 14: 7. What is Machine Learning

Lecture 15: Summary

Instructors

DATAhill Solutions Srinivas Reddy
Data Scientist

Rating Distribution

1 stars: 14 votes

2 stars: 16 votes

3 stars: 55 votes

4 stars: 72 votes

5 stars: 56 votes

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