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.
Enroll now: Numpy with Python
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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