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Python3 Pandas Datascience Timeseries

Course

PYTHON3 PANDAS DATASCIENCE TIMESERIES

Category

Python and Data Science IT Training

Eligibility

Technology Learners

Mode

Both Classroom and Online Classes

Batches

Week Days and Week Ends

Duration :

60 Days

Python and Data Science What will you learn?

•An overview about Python and Data Science concepts.
•Learn Python and Data Science proficiently in a structured fashion.
•Learn Python and Data Science from scratch. Code like a PRO
•Learn how to structure a large-scale project using Python and Data Science.
•Learn or brush up with the basics of Python and Data Science
•Learn Python and Data Science at your own pace with quality learning videos.
•This course will teach you how to get moving in Python and Data Science.
•How to handle different types of data inside a workflow using Python and Data Science.
•Learn the essential skills to level-up from beginner to advanced Python and Data Science developer in 2021!

python3 pandas datascience timeseries Training Highlights

•Free Aptitude classes & Mock interviews
•Basic Training starting with fundamentals
• Helps you stand out in a competitive market
•We enage Experienced trainers for Quality Training
•Highly Experienced Trainer with 10+ Years in MNC Company
•Training by Proficient Trainers with more than a decade of experience
•Training time :  Week Day / Week End – Any Day Any Time – Students can come and study
•We help the students in building the resume boost their knowledge by providing useful Interview tips

Who are eligible for Python and Data Science

•Architect, Program Manager, Delivery Head, Technical Specialist, developer, Sr. Developer, Transition Manager, Quality Manager, Consultant
•Iot, Embedded Systems, Bluetooth Low Energy, Bluetooth, Web Designing, Responsive Web Design, Visual Web Developer, Aws, Cloud Computing, Algorithm
•Java, Scrum Master, Agile, C#, It, Al, Big Data, Hadoop, .Net, Non It, It Recruitment, Ios, Android, React, Web Designing, Selenium, Testing, Qa, Cloud
•scala, React.js, Backend Developers, Frontend Developers, Fullstack Developers, Ui/ux Designers, Test Engineering, Site Reliability Engineer, Machine Learning
•Software Development, .net, java, Asp.net, Sql Server, database, Software Testing, javascript, Agile Methodology, Cloud Computing, html, application

PYTHON3 PANDAS DATASCIENCE TIMESERIES Topics

Objectives, Prerequisites, and Audience
•Course Topics Overview
•Please Leave your feedback
•Scientific Python Ecosystem
•Important URLs
•Python 3 on Windows
•Verify Python 3 environment on Windows
•Python 3 on Raspberry Pi
•What is Raspberry Pi
•Unboxing
•Important URLs used in the Setup of Raspberry Pi
•Raspbian OS Setup on Raspberry Pi Part 1
•Raspbian OS Setup on Raspberry Pi Part 2
•Remotely connect to RPi with VNC
•Commands used in the section
•Install IDLE3 on Raspberry Pi Raspbian
•Python 3 Basics
•Hello World! on Windows
•Hello World! on Raspberry Pi
•Interpreter vs Script Mode
•IDLE
•Raspberry Pi vs PC
•Python 3 and PyPI
•PyPI and pip
•pip on Windows
•pip3 on Raspberry Pi
•Installing NumPy and Matplotlib
•Install NumPy and Matplotlib on Windows
•Install NumPy and Matplotlib on Raspberry Pi
•Jupyter Notebook
•Jupyter and IPython
•Jupyter Installation on Windows
•Jupyter Installation on Raspberry Pi
•Remote connection with PuTTY
•Connect to a remote Jupyter Notebook
•A brief tour of Jupyter
•Getting Started with NumPy
•Introduction to NumPy
•Ndarrays, Indexing and Slicing
•Ndarray Properties
•NumPy Constants
•NumPy Datatypes
•Array creation routines
•Ones and Zeros
•Matrices
•Introduction to Matplotlib
•Numerical Ranges and Matplotlib
•Random Sampling
•Array Manipulation
•Bitwise Operation
•Statistical Functions
•Plotting in Detail
•Single Line Plots
•Multiline Plots
•Grid Axes and Labels
•Color Line Markers
•Installing SciPy and Pandas
•Introduction to SciPy
•Install SciPy on Windows
•Install SciPy on Raspberry Pi
•Introduction to Pandas
•Install Pandas on Windows
•Install Pandas on Raspberry Pi
•Matrices and Linear Algebra
•Dot Products
•Vector and Dot Products
•Inner Products
•QR Decomposition
•Determinants and Solving Linear Equations
•Linear Algebra with SciPy
•Data Acquisition with Python, NumPy, and Matplotlib
•Plain Text File Handling
•CSV
•Excel File
•NumPy file format
•Read a CSV file with NumPy
•Matplotlib CBook
•Python and MySQL
•MySQL installation on Windows
•Getting Started with MySQL and SQL Workbench
•Install SQL Developer on Windows
•Connect to MySQL with SQL Developer
•Exploring MySQL Workbench
•Pymysql installation on Windows
•Connect to MySQL with Python 3
•DDL
•INSERT
•SELECT
•UPDATE
•DELETE
•DROP
•Dataframes and Series in Pandas
•Series
•Dataframe
•Data Acquisition with Pandas
•Read data from a CSV file
•Read an excel file
•Read from JSON
•Pickles
•Read data from Web
•Read data from SQL
•Read from Clipboard
•Time Series in Pandas
•Datetime in Python 3
•Introduction to the Time Series
•Shifting and Timezone Handling
•Time Series Analysis with More libraries
•Plotly
•Plotly and Matplotlib
•Seaborn
•Altair
•Visualize the financial data
•Candlestick
•Open High Low Close Charts
•More Time Series
•Time Series Basics Revisited
•Complete Time Series Analysis : Example 1
•Downloadable Resources and Code Bundle
•Code Bundle