English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 6.5 Hours | 2.89 GB
Learn about the exciting field of IoT with Advanced Python programming.
IoT is bringing more and more things into the digital fold every day, which will likely make it a multi-trillion dollar industry in the near future. Building your own project on IoT will help you practically learn how engineering is applied on this amazing technology.
For the development of an IoT solution, one would need a programming language which while being lightweight and scalable at the same time. One such is Python and we are going to learn how to implement the same with this training.
Learn about the exciting field of IoT with Advanced Python programming.
The training will include the following;
- Using in-built standard modules in python (datetime, math, statistics)
- Networking using sockets
- Using apis for twitter and emails
- Data science modules for iot (numpy, scipy, pandas, matplotlib)
- Multi-threading and Exception handling
Table of Contents
Introduction
1 Introduction to Packages and Modules
Installation
2 Concept of Anaconda Distribution
3 Installation of PyCharm
Nuts and Bolts
4 Executing Programs in PyCharm
5 Methods of the List
6 Learning the Bolt Structure
Networking and Networking Concepts
7 Networking Aspect of Client Server
8 Mesaage Communication of Client and Server
9 Server IP from Client to Server
Socket Programming
10 Programming Aspect of Networking
11 Writing the Client and Server Code
12 Socket Programming for Server
13 Python Package for Multithreading
ChatBot App
14 Working with Chat Bot
15 Sending and Receiving Data
16 Working on Chat Bot Server
17 Creating and Importing Client Socket
18 Creating Message for Client
19 Learning to Create a Chat App
Database and Chat App
20 Pycharm Databases and Sqlite
21 Commands for Creating a Table
22 Inserting Values in Table
23 Connecting Between Database and Python Code
24 Query from Database
25 Making changes in Chat App
26 Decoding the Client info
Client Element and Datasets
27 Indexing the Client Element
28 Connection from Client at Address
29 Adding Email and Client Name
30 Analyzing the Data Sets
31 Coding for Converting Tempratures
32 Converting Temperature using List comprehension
Numpy
33 Introduction to Numpy
34 Size of List
35 Memory Consumed By Ndarray
36 Python List and Numpy Arrays
Numpy Arrays
37 Creating Numpy Arrays
38 Different Dimensional Array in Numpy
39 Shape of an Array
40 Slicing
41 Slicing Continue
42 Arrays of Ones and Zeros
43 Numpy Example
44 Numpy Example Continue
45 Using Scalers with Numpy Arrays
46 Matrix Multiplication
47 Comparison Operations
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