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Data Analysis With Python A Complete Guide 4 In 1




Python Professional Course


All Job Seekers


Both Classroom and Online Classes


Week Days and Week Ends

Duration :

60 Days

Python What will you learn?

•Learn to write PythonFunctions.
•Explore how to use existing features in Python.Learn how to develop, build and deploy Python
•Learn how to structure a large-scale project using Python.
•Learn Python programming best pracitices, SOLID, Design and more!
•Learn fundamentals of Python for Beginners: Practical and hands-on learning
•An easy way to learn one of the widely used Python
•How to setup a Python script and Interface in real time development.
•with this time saving course you will Learn Python and ready to use it

data analysis with python a complete guide 4 in 1 Training Highlights

•Real-world skills + project portfolio
•Free technical support for students
•Accessibility of adequate training resources
•Immersive hands-on training on Python Programming
•We provide Classroom and Online training in Metro Cities
•Access to a huge closet containing information about Hadoop
•We provide one to one mentorship for the students and Working Professionals
•We help the students in building the resume boost their knowledge by providing useful Interview tips

Who are eligible for Python

•.net, front end developer, Android Development, ios, Big Data, Web Development, java full stack, Service Now, Wintel Servers, Change Management, Database
•Digital Marketing, General Manager, Business Development, Product Manager, Big Data, Business Analyst, Frontend Developer, Human Resources, data
•java, php, .net, 3dmodelling, unitydeveloper, androiddeveloper, gamedeveloper, Software Developer, Php, Java, Photoshop
•Qa Automation, Ror Developer, Android Developer, Bluetooth Developer, Android Application Developer, Embedded Development, Javascript, Ruby, Postgres, SQL
•WCS, Hybris, ATG, Java, Linux Administrator, mobile, ECommerce Technologies, Testing, UI, Big Data, Cloud, iOS, Android


Learning Python Data Analysis
•The Course Overview
•Getting started with Python
•Getting Data using the Twitter API
•Collecting and Storing Tweets
•Database Design
•Pandas and Databases
•Panda Series, Dataframes, and Columnar Operations
•Grouping Operations and Working with Date Columns
•Merging Operations and Exporting data to JSON/CSV
•Array Features, Bucketting Arrays and Histogram Functions
•Simple Aggregations
•Linear Algebra
•Introducting PyQT and MatplotLib
•Creating Charts
•Simple XY Plots with Axis Scales
•Bag of Words
•Classification of Words
•Simple Sentiment Analysis
•Grouping By Dimensions and Classification of Data Types
•Trend Analysis and Deriving New Metrics
•Correlation Analysis
•Course Summary
•Test your knowledge
•Data Analysis with Python
•Python Core Concepts and Data Types
•Understanding Iterables
•List Comprehensions
•Dates and Times
•Accessing Raw Data
•Creating NumPy Arrays
•Basic Stats and Linear Algebra
•Reshaping, Indexing, and Slicing
•Getting Started with Pandas
•Essential Operations with Data Frames
•Data Aggregation Over a Data Frame
•Titanic Survivor Analysis
•Predicting Titanic survival – A Supervised Learning Problem
•Performing Supervised Learning with Scikit-Learn
•Become a Python Data Analyst
•The Anaconda Distribution
•Using the Jupyter Notebook
•NumPy: Python’s Vectorization Solution
•NumPy Arrays: Creation, Methods and Attributes
•Using NumPy for Simulations
•The Pandas Library
•Main Properties, Operations and Manipulations
•Answering Simple Questions about a Dataset –
•Basics of Matplotlib
•The Object Oriented Interface
•Common Customizations
•EDA with Seaborn and Pandas
•Analysing Variables Individually
•Relationships between Variables
•SciPy and the Statistics Sub-Package
•Alcohol Consumption – Confidence Intervals and Probability Calculations
•Hypothesis Testing – Does Alcohol Consumption Affect Academic Performance?
•Hypothesis Testing – Do Male Teenagers Drink More Than Females?
•The Scikit-Learn Library – Building a Simple Predictive Model
•Classification – Predicting the Drinking Habits of Teenagers
•Regression – Predicting House Prices
•Data Acquisition and Manipulation with Python
•Getting Data in Its Different Formats
•Connecting to a Database
•Adding Information to a Database
•Query a Database
•Combining and Merging Datasets
•Reshaping Data
•Data Transformation
•String Manipulation
•Grouping Basics
•Data Aggregation
•GroupWise Operations and Transformations
•Pivot Tables and Cross Tabulation
•Exploring Web Scraping
•Scraping the Web Safely
•Let’s Have a BeautifulSoup
•Downloading and Reading a Webpage
•Extracting Useful Information
•Making Use of Selenium
•Navigating the Web with Selenium
•Extracting Information with Selenium
•Diving into Scrapy
•Creating a Scrapy Spider
•Programming a Spider
•Introduction to the NTLK Package