Data Science & Python_ Maths, Python Libraries, Statistics

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Data Science & Python: Maths, Python Libraries, Statistics
Published 07/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.67 GB | Duration: 79 lectures • 13h 6m



What you'll learn
What is Python
Uses of Python
How to write code in Python
What are Python libraries
What is Anaconda
What is Jupyter Notebook
What is Numpy
What is Matplotllib
How to plot in Matplotlib
What is Scipy
What is Scikit
What is Pandas
How to import files in Jypyter notebook using Pandas
How to create files using Pandas
Basic math in Python
Linear Algebra in Pythom
Statistics in Python
2d and 3d plotting in Python
Linear regression in Python
differential and Integral calculus in Python
Development
Data Science
Data Science & Python: Maths, Python Libraries, Statistics
Learn Python, Numpy, Pandas, Matplotlib, Linear Regression, Algebra, Statistics, Calculus, Projects & Data Visualisation
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2 students
Created by ,
Published 7/2022
English
English[Auto]


What you'll learn
What is Python
Uses of Python
How to write code in Python
What are Python libraries
What is Anaconda
What is Jupyter Notebook
What is Numpy
What is Matplotllib
How to plot in Matplotlib
What is Scipy
What is Scikit
What is Pandas
How to import files in Jypyter notebook using Pandas
How to create files using Pandas
Basic math in Python
Linear Algebra in Pythom
Statistics in Python
2d and 3d plotting in Python
Linear regression in Python
differential and Integral calculus in Python
Course content
13 sections • 79 lectures • 13h 6m total length
Preview
01:55
Preview
04:22
Introduce Yourself To Your Fellow Students And Tell Everyone What Are Your Goals
00:17
Let's Celebrate Your Progress In This Course: 25% > 50% > 75% > 100%!!
01:20
Download your project files: Pandas, NumPy & Matplotlib
00:14
Requirements
Internet connection
Laptop or PC or Mobile Phone
Motivation towards new learning

Description
Get instant access to a 73-page workbook on Data Science, follow along, and keep for reference
Introduce yourself to our community of students in this course and tell us your goals with data science
Encouragement and celebration of your progress every step of the way: 25% > 50% > 75% & 100%
Over 13 hours of clear and concise step-by-step instructions, lessons, and engagement
This data science course provides participants with the knowledge, skills, and experience associated with Data Science. Students will explore a range of data science tools, algorithms, linear programming and statistical techniques, with the aim of discovering hidden insights and patterns from raw data in order to inform scientific business decision-making.
What you will learn
Introduction to Python; what is Python, Anaconda, libraries, Numpy, Matplotlib, SciPy and SciKit Learn
Learn mathematics by coding in python; basic maths, variables. solutions of equations. logarithmic and exponential functions. polynomials, complex numbers and trigonometry
Statistics by coding in Python
Linear Algebra for data science: matrices. determinants, inverse, solutions, scalars and vectors
Detailed introduction and demo of Numpy
Linear algebra in Python as well as calculus. Matplotlib and more
Lear Data Science projects in Pandas: importing files, creating data frames
Regression analysis using SKLearn
Data science careers in a Q&A Webinar plus additional insights; learn from other students questions
Who are the Instructors?
Dr. Allah Dittah is your lead instructor - a PhD and lecturer making a living from teaching Python, advanced mathematics and data science. As a data science expert, he has joined with content creator Peter Alkema to bring you this amazing new course.
You'll get premium support and feedback to help you become more confident with data science!
We can't wait to see you on the course!
Enrol now, and we'll help you improve your data science skills!
Peter and Allah
Who this course is for
For those who love with learning
Data scientists
For those who want to apply Python in a practical way in their organization

 

 

 

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Edited December 23, 2022 by Bad Karma
Dead links removed