Location:Main Road, Bangalore


Python And Pandas Data Science And Visualization Masterclass




Python and Data Science Professional Training


Freshers and Career Changers


Regular Offline and Online Live Training


Week Days and Week Ends

Duration :

1.5  hrs in weekdays and 3hrs during Weekend

Python and Data Science Objectives

•Learn about Python and Data Science Practices and guidelines.
•What are the advantages of Python and Data Science?
•A Beginner’s Guide to Python and Data Science Coding from scratch
•Learn how to structure a large-scale project using Python and Data Science.
•Step by step tutorial to help you learn Python and Data ScienceLearn how to get a Job as a Python and Data Science developer .
•Learn how to implement the all the functionalities of a Python and Data Science.
•Learn Python and Data Science the Fast and Easy Way With This Popular Bundle Course!
•Learn the essential skills to level-up from beginner to advanced Python and Data Science developer in 2021!

python and pandas data science and visualization masterclass Training Features

•24 × 7 = 365 days supportive faculty
•Get Training from Certified Professionals
•We assist on Internship on Real-Time Project 
•Regular Brush-up Sessions of the previous classes
•Fast track and Sunday Batches available on request
•Project manager can be assigned to track candidates’ performance
•One-on-one training, online training, team or Corporate training can be provided
•This Instructor-led classroom course is designed with an aim to build theoretical knowledge supplemented by ample hands-on lab exercises

Who are eligible for Python and Data Science

•Application Server, Problem Mgmt, SAP Technical/Functional, BO Developer, Automotive Developer, Protocols, Embedded C, AutoSar, Window Applications
•Data Analysis, Data Management, Data Mining, Specification Writing, Software Developer, DBA Consultant, Content Writer, .PHP, .NET, Developer, Network
•Java Developer, Quality Assurance, Core Java, Spring Mvc, Spring Boot, hibernate, jpa, Web Services, json, maven, angularjs, mysql, Sql Server, Tomcat, Uml
•php, wordpress, drupal, Iphone Developer, Android, Java, Team Management, Android Developer, Mobile Application Development
•UI/Web Developer, UX Designer, Java Developer, PHP Developer, IOS/Android Developer, Business Development Executive, .NET Developer, .NET Lead, PHP Lead


•Objectives, Prerequisites, and Audience
•Course Topics Overview
•Scientific Python Ecosystem
•URLs of important projects in SciPy Ecosystem
•Please leave your feedback
•Python 3 on Windows
•Installation on Windows
•Verify the installation
•Python 3 on Raspberry Pi
•What is Raspberry Pi?
•Web URLs for Software Download
•Raspberry Pi Raspbian OS Setup Part 1
•Raspberry Pi Raspbian OS Setup Part 2
•Remote Connection with VNC
•Commands used in this Section
•Install IDLE3 on Raspberry Pi Raspbian
•Python 3 Basics
•”Hello World!” on Windows
•”Hello World!” on Raspberry Pi
•Interpreter vs Script Mode
•Comparison of RPi with other computing platforms
•Python Package Index and pip3
•Python Package Index
•pip on Windows
•pip3 on Raspberry Pi
•NumPy and Matplotlib installation
•NumPy and Matplotlib installation on Windows
•NumPy and Matplotlib installation on Raspberry Pi
•Jupyter Notebook Basics
•Jupyter and IPython
•Jupyter installation on Windows
•Jupyter installation on Raspberry Pi
•PuTTY installation on Windows
•Connect to remote Jupyter notebook
•A brief tour of Jupyter
•Getting Started with NumPy
•Introduction to NumPy
•Ndarray Indexing and Slicing
•Ndarrays Properties
•NumPy Constants
•NumPy Datatypes
•Creation of Arrays and Matplotlib Visualizations
•Ones and Zeros
•Introduction to Matplotlib
•Numerical Ranges and Visualizations
•NumPy and Random
•Ndarray Manipulation Routines
•Bitwise Operations
•Statistical Functions
•Plotting in Detail
•Single Line Plots
•Multiline Plots
•Grid, Axes, and Labels
•Colors, Lines, and Markers
•Installing SciPy and Pandas
•Introduction to SciPy
•Install SciPy on Windows
•Install SciPy on Raspberry Pi
•What is Pandas?
•Install Pandas on Windows
•Install Pandas on Raspberry Pi
•Matrices and Linear Algebra
•Dot Products
•Vector Dot Products
•Inner Products
•QR Decomposition
•Determinants and Solving Linear Equations
•Linear Algebra
•Data Acquisition with Python, NumPy, and Matplotlib
•Plain Text File
•Handling Excel File
•NumPy File Format
•NumPy CSV File Reading
•Matplotlib CBook
•MySQL and Python
•Installation of MySQL on Windows
•Getting Started with MySQL and SQL Workbench
•SQL Developer Installation Guide
•Connect to MySQL with SQL Developer
•Explore MySQL Workbench
•pymysql Installation on Windows
•Connect to MySQL with Python 3
•Execute DDL
•Series and Dataframe in Pandas
•Data Acquisition with Pandas
•Read CSV
•Read Excel
•Read JSON
•Pandas and Web
•Read SQL
•Data Cleaning with Pandas
•Data Analysis with Pandas
•Hierarchical Indexing
•More Data Science with Pandas
•Database Style Joins
•Merge on Index
•Group By
•Data Visualization with Pandas
•Data Visualization with Pandas Part 1
•Data Visualization with Pandas Part 2
•Data Visualization with Pandas Part 3
•Data Visualization with Seaborn
•A complete data science example
•A bit of Machine Learning
•Advanced Pandas
•Concat aling Axis
•Combine Data with Overlap
•Operations on Strings
•Panels in Pandas
•Time Series in Pandas
•Shifting and Timezone Handling
•plot.ly Basics
•Scatter Plot
•Bubble Chart
•Line Plots
•Area Plots
•Bar Chart
•Horizontal Bar Chart
•Gantt Chart
•Pie Chart
•Ploy.ly and Pandas
•Scatter Graphs
•Line Charts
•Error Bar
•Box Plot
•Basic Histogram
•2D Histogram
•Inset Plots
•Gantt Charts
•More Pandas Concepts
•Descriptive Analysis in Pandas
•Categorical Data
•Sparse Data and Pandas
•Truth Statement in pandas
•Downloadable Contents
•Code Bundle