Data Manipulation in Python: Master Python, Numpy & Pandas
Learn Python, NumPy & Pandas for Data Science: Master essential data manipulation for data science in python
Development,Data Science,Python,Database Programming
Lectures -107
Resources -12
Duration -3.5 hours
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Course Description
When it comes to being attractive, data scientists are already there. In a highly competitive job market, it is tough to keep them after they have been hired. People with a unique mix of scientific training, computer expertise, and analytical abilities are hard to find.
Like the Wall Street "quants" of the 1980s and 1990s, modern-day data scientists are expected to have a similar skill set. People with a background in physics and mathematics flocked to investment banks and hedge funds in those days because they could come up with novel algorithms and data methods.
That being said, data science is becoming one of the most well-suited occupations for success in the twenty-first century. It is computerized, programming-driven, and analytical in nature. Consequently, it comes as no surprise that the need for data scientists has been increasing in the employment market over the last several years.
The supply, on the other hand, has been quite restricted. It is challenging to get the knowledge and abilities required to be recruited as a data scientist.
Lots of resources for learning Python are available online. Because of this, students frequently get overwhelmed by Python's high learning curve.
It's a whole new ball game in here! Step-by-step instruction is the hallmark of this course. Throughout each subsequent lesson, we continue to build on what we've previously learned. Our goal is to equip you with all the tools and skills you need to master Python, Numpy & Pandas.
You'll walk away from each video with a fresh idea that you can put to use right away!
All skill levels are welcome in this course, and even if you have no prior programming or statistical experience, you will be able to succeed!
Who this course is for:
- No previous skills or expertise is required. Only a drive to succeed!
Goals
What will you learn in this course:
Learn to use Pandas for Data Analysis
Learn to work with numerical data in Python
Learn statistics and math with Python
Learn how to code in Jupyter Notebook
Learn how to install packages in Python
Prerequisites
What are the prerequisites for this course?
No prior data science knowledge required
No programming experience needed
Curriculum
Check out the detailed breakdown of what’s inside the course
Python Quick Refresher (Optional)
21 Lectures
- Welcome to the course! 00:36 00:36
- Introduction to Python 00:52 00:52
- Resources
- Setting up Python 02:24 02:24
- What is Jupyter? 00:59 00:59
- Anaconda Installation: Windows, Mac & Ubuntu 04:15 04:15
- How to implement Python in Jupyter? 00:44 00:44
- Managing Directories in Jupyter Notebook 02:48 02:48
- Input/Output 01:44 01:44
- Working with different datatypes 01:05 01:05
- Variables 01:50 01:50
- Arithmetic Operators 01:48 01:48
- Comparison Operators 00:43 00:43
- Logical Operators 03:05 03:05
- Conditional statements 02:20 02:20
- Loops 04:30 04:30
- Sequences: Lists 03:18 03:18
- Sequences: Dictionaries 02:48 02:48
- Sequences: Tuples 01:07 01:07
- Functions: Built-in Functions 00:26 00:26
- Functions: User-defined Functions 03:14 03:14
Essential Python Libraries for Data Science
7 Lectures
Fundamental NumPy Properties
5 Lectures
Mathematics for Data Science
15 Lectures
Python Pandas DataFrames & Series
22 Lectures
Data Cleaning
10 Lectures
Data Visualization using Python
12 Lectures
Exploratory Data Analysis
10 Lectures
Time Series in Python
5 Lectures
Instructor Details
Meta Brains
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