What is data analytics with Python?

Data analytics with Python is the process of analyzing data using the Python programming language. It involves using Python libraries and tools to extract insights from large data sets.

What are the job prospects for someone with data analytics with Python skills?

The demand for data analysts with Python skills is growing rapidly in many industries, including finance, healthcare, marketing, and technology. Jobs that require data analytics with Python skills can include data analyst, data scientist, machine learning engineer, and business intelligence analyst.

PTN-109: Data Analytics with Python

Name: PTN-109: Data Analytics with Python
Brand: Python

RM3,000.00

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This Python training is designed to teach you how to use Python for data analytics. With the vast amounts of data being generated each day, Python has become an essential tool for data analysts.

In this course, you will explore the latest Python tools and techniques for data acquisition and analysis, including scientific computing with NumPy and data visualization with matplotlib. Prerequisites for the course include a basic understanding of Python and data analytics.

The course is aimed at Python programmers who want to work with data analytics.

Training Duration: 2 Days

Certificate Of Completion Available
Group Private Class
VILT Class Available
SBL-Khas Claimable

Download Course Outline

In a world increasingly centralized around information technology, huge amounts of data are produced and stored each day. Often these data come from automatic detection systems, sensors, and scientific instrumentation, or you produce them daily and unconsciously every time you make a withdrawal from the bank or make a purchase, when you record various blogs, or even when you post on social networks.

Python and its supporting packages are one of the famous tools in dealing with Data Analytics. This is the course to guide you how to use Python in Data Analytics.

This course will let you explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You will review scientific computing with NumPy and visualization with matplotlib.
A basic understanding of Python language.

A basic understanding of Data Analytics will be an added advantage.
Module 1 - An Introduction to Data Analysis

Data Analysis

Knowledge Domains of the Data Analyst

Understanding the Nature of the Data

The Data Analysis Process

Quantitative and Qualitative Data Analysis

Open Data

Python and Data Analysis

Module 2 – Introduction to the Python World

The Language

Python 2 and Python 3

The IDEs for Python

Packages for Data Analysis

Module 3 – The NumPy Library

The History

Ndarray: The Heart of the Library

Basic Operations

Indexing, Slicing, and Iterating

Conditions and Boolean Arrays

Shape Manipulation

Array Manipulation

General Concepts

Structured Arrays

Reading and Writing Array Data on Files

Module 4 – The Pandas Library—AnIntroduction

pandas: The Python Data Analysis Library

Installation of pandas

Testing Your pandas Installation

Getting Started with pandas

Introduction to pandas Data Structures

Other Functionalities on Indexes

Operations Between Data Structures

Function Application and Mapping

Sorting and Ranking

Correlation and Covariance

“Not a Number” Data

Hierarchical Indexing and Leveling

Module 5 – Pandas: Reading and Writing Data

I/O API Tools

CSV and Textual Files

Reading Data in CSV or Text Files

Reading and Writing HTML Files

Reading Data from XML

Reading and Writing Data on Microsoft Excel Files

JSON Data

The Format HDF5

Pickle—Python Object Serialization

Interacting with Databases

Reading and Writing Data with a NoSQL Database: MongoDB

Module 6 – Pandas in Depth: Data

Manipulation

Data Preparation

Concatenating

Data Transformation

Discretization and Binning

Permutation

String Manipulation

Data Aggregation

Group Iteration

Advanced Data Aggregation

Module 7 – Data Visualization with matplotlib

The matplotlib Library

The IPython and IPython QtConsole

The matplotlib Architecture

pyplot

The Plotting Window

Using the kwargs

Adding Elements to the Chart

Saving Your Charts

Handling Date Values

Chart Typology

Line Charts

Histograms

Bar Charts

Pie Charts

Advanced Charts

The mplot3d Toolkit

Multi-Panel Plots
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What is data analytics with Python?

Data analytics with Python is the process of analyzing data using the Python programming language. It involves using Python libraries and tools to extract insights from large data sets.

Why should I learn data analytics with Python?

Python is a popular programming language for data analytics because it is easy to learn, has a large community of users, and has a vast collection of libraries and tools for data analysis. By learning data analytics with Python, you can gain valuable skills for a career in data analysis or use data analytics to gain insights in your personal or professional life.

What are the job prospects for someone with data analytics with Python skills?

The demand for data analysts with Python skills is growing rapidly in many industries, including finance, healthcare, marketing, and technology. Jobs that require data analytics with Python skills can include data analyst, data scientist, machine learning engineer, and business intelligence analyst.
Are you looking to take your career to the next level? Python training and certification can be the perfect way to give your resume a competitive edge and open up new opportunities in the tech industry.

Python is a popular and powerful programming language that is widely used in a variety of industries, including finance, data analysis, and web development. With its versatility and growing demand, investing in Python training and certification can be a valuable asset for professionals looking to advance their careers.

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PTN-109: Data Analytics with Python

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