Published 06/2022
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 702 MB | Duration: 25 lectures • 1h 55m
NumPy for Data Science and Machine Learning in Python PostgrSQL course for beginners and first-time coders
What you’ll learn
Basics of Numpy, Arrays, Lists.
Accessing/Changing Specific Elements, Rows, Columns, etc
Initializing Different Arrays (1s, 0s, full, random, etc)
Basic Mathematics (arithmetic, trigonometry, etc.)
Linear Algebra and Statistics
Create your own database or interact with existing databases
You will write basic to advance PostgreSQL queries
Troubleshoot everyday PostgreSQL database related issues
Have a detailed knowledge and understanding of using MySQL, one of the most widely used databases in the world.
Requirements
Basic Python
Description
Welcome! This is Numpy and PostgreSQL for Beginners course.
One question or concern I get a lot is that people want to learn deep learning and data science, so they take these courses, but they get left behind because they don’t know enough about the Numpy stack in order to turn those concepts into code.
Even if I write the code in full, if you don’t know Numpy, then it’s still very hard to read.
This course is designed to remove that obstacle – to show you how to do things in the Numpy stack that are frequently needed in deep learning and data science.
So what are those things?
Numpy. This forms the basis for everything else. The central object in Numpy is the Numpy array, on which you can do various operations.
The key is that a Numpy array isn’t just a regular array you’d see in a language like Java or C++, but instead is like a mathematical object like a vector or a matrix.
That means you can do vector and matrix operations like addition, subtraction, and multiplication.
The most important aspect of Numpy arrays is that they are optimized for speed. So we’re going to do a demo where I prove to you that using a Numpy vectorized operation is faster than using a Python list.
Then we’ll look at some more complicated matrix operations, like products, inverses, determinants, and solving linear systems.
If you want to learn how to gain insights from data but are too intimidated by databases to know where to start, then this course is for you. This course is a gentle but comprehensive introduction to MySQL, one of the most highly in-demand skills in the business sector today.
Help you understand and apply PostgreSQL , including Database Design and Data Analysis.
Having database skills is absolutely vital for developers to avoid getting left behind and to maximize job and consulting opportunities.
Key concepts you will learn and work on within this course.
SQL (Structured Query Language – very much an in-demand technology).
PostgreSQL (one of the world’s most popular and widely used databases).
Database Design
Data Analysis
Content of the course.
Creating, Modifying, and Deleting Tables in a Database
Inserting, Updating, and Deleting Data from Tables
Select Queries
Aggregate Functions
Creating Databases.
Who this course is for
Anyone interested in learning PostgreSQL to help with their current job or to find a new role. PostgreSQL is one of today’s most in-demand skills
Anyone looking to answer complex business problems and generate reports using data
Business owners, people in sales, or people in marketing roles who are interested in understanding company data better.
Developers who are looking to build applications (e.g. social network, e-commerce site) using PostgreSQL
Your new job or consulting opportunity awaits!
Why not get started today?
Click the Signup button to sign up for the course!
Who this course is for
Students and professionals with little Numpy experience who plan to learn deep learning and machine learning later
Students and professionals who have tried machine learning and data science but are having trouble putting the ideas down in code
Anyone interested in learning more about SQL, PostgreSQL, or basic data analysis!
Anyone interested in data analysis
Anyone who wants to learn about database and data management systems
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