Python Data Analytics

Course Duration : 90 Hours, Course Fee : 30000

Learn Python Data Analytics with main coverage of Python Panda Module. Get the thorough insights on implementing each modules and using it in a daily routine. Register for free demo @ +91-72899 89188

The Python Data Analytics training is designed to teaches engineers, data scientists, statisticians, and other quantitative professionals the Python skills they need to use with the Python programming language to analyze and creating customized chart as per the actual data.

Candidates are suggested to opt for basic python training by ACLM to set career in Python Data Analytics, Python based Web Framework and Python Artificial Intelligence.

Python Data Analytics Training, Objective & Outcomes:

Learn about previous Python versions. Similarities and differences
Data Types in Python, learn about lists, tuples, dictionary and many more
Creating variables, declaring global and local variables and reusing variables
Creating mixed data sets with various data types in python
Generating sequential and random number series in numerics, date, time
Learn to generate binary, hexacodes using python with various exercises
Learn to create python modules, classes
Creating and implementing existing python collections
Design and create python parametric and non-parametric functions
Looping and Data Flow in Python, learn to play with various loops
Exception handling in python, learn to use {try} {except} block in python
Practice sessions with the help of assignments, notes and assessment
File handling in python with various unorganized data in python like csv, txt, tbdl and many more
Data handling with the help of Pandas python framework
Learn to installing and un-installing external python libraries
Using external libraries like pandas, dataframe(df), numpy skypy, ndarrays and xlrd
Identifying bad data / missing data and data cleaning technique with the help of python
Creating Graphs, Charts, Maps in Python for GUI representation
Merging various data sets in python
Data statistics in python: learn linear regression, data modelling, differentiation, T-Test, F-Test, Sampling, Co-relations and many more
Machine Learning (ML) and various other approaches to statistics

So, What’s waiting for, just register yourself and start exploring the world by this tailor-made training on python data analytics. You can also register by dropping a mail to info@aclm.in or call us @ 9718812233

Topics Covered

PYTHON DATA ANALYTICS COURSE OUTLINE

Python Introduction

Comparison of Python with other languages and prior history
Strings and Numbers in python
Data Structures in Python using lists, tuples & Dictionary
The powerful Datetime Module in Python
Handling Data and Memory in Python
Various data flow control in python (While, Do Loop, For and For Each)
Usage of Functions in Python (Parametric Vs. Non-parametric)
Error or Exception Handling in Python

Handling data: Query and Questionnaire

Assignment 1 on Binary, Decimal and Hexacodes
Assignment 2: Handling inputs through looping, multiple question
Assignment 3: String handling in python. The interactive 32 questions in python
Correcting bad Data in Python with various methods

Reading / Writing Data Files

Reading / writing Structured Data
Working with Unstructured Data Types (CSV, TBDL, XML, XLS and many more)

Handling Data with NumPy

Installing and activating NumPy
Handling 1D, 2D and ND Array Data
Using Axis Parameters
Deploying NumPy Data
Handling Bad / Missing data in NumPy

Data Analytics with Pandas

Sorting and Filtering Raw Data using Pandas
Defining your own variable
Data Frames and Series
Accessing elements by Index
Reading and Writing
Agreegating and Grouping in Pandas
Pivoting tables in Pandas
Time Series Analysis in Pandas
Visualization in Pandas
Statistical Analysis using Pandas
Assignments 1: on Pandas Data Handling
Assignment 2: on Pandas Data Framing and Pivoting
Assignemnt 3: Pandas Stats Problem solving exercises

Representing Data graphically

To get a little overview here are a few popular plotting libraries:

Matplotlib: low level, provides lots of freedom
Pandas Visualization: easy to use interface, built on Matplotlib
Seaborn: high-level interface, great default styles
ggplot: based on R’s ggplot2, uses Grammar of Graphics
Plotly: can create interactive plots

Multivariate Statistics

Linear Regression
Logistic regression

Who Should Attend

Python Data Analytics training is designed for data engineers, data scientists, statisticians, and other quantitative professionals.

Pre-requisites

What You Need To Bring

Anaconda Python 3.5
Spyder IDE (Comes with Anaconda)
For classes delivered online, all participants need either dual monitors or a separate device logged into the online session so that they can do their work on one screen and watch the instructor on the other. A separate computer connected to a projector or large screen TV would be another way for students to see the instructor's screen simultaneously with working on their own.

Key Takeaways

Strong Analytics Skill in Python

About Trainer

International Certifications on Python Pandas, NumPi, XLRD
Microsoft certified trainer
Certified Azure cloud network engineer
12+ Years in Data Analysis, Reporting and Automation

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