Business Analytics with Python Training

Live Online & Classroom Enterprise Training

Master the advanced business analytics concepts to improve your organization's performance. Learn to create analytics solutions to derive insights from enterprise data using powerful functions and libraries in Python. Become the lead business analytics professional your team needs.

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Enterprise Reporting
Lifetime Access
CloudLabs
24x7 Support
Real-time code analysis and feedback

What is Business Analytics Python Training about?

Master the quantitative methods to analyze data using readily available functions and libraries such as NumPy, Pandas, and SciPy for data analysis in Python. Gain the deep understanding of statistical techniques, modern data mining, pattern matching, data visualization, exploratory and predictive modeling. Produce actionable insights from enterprise and public information.

In our Cloudlabs, implement the statistical tools for data analysis through readily available Python functions and libraries. Create algorithms and models to either validate or predict the outcomes of various business decisions and be able to identify the best implementation.

Be the lead data analyst that your organization needs.

What are the objectives of Business Analytics Python Training ?

After completing our Business Analytics with Python training, you will be able to:

Develop analytical approach to management to utilize data, understand statistical and quantitative models
Recognize trends, detect outliers, and summarize data sets concisely
Develop and test hypotheses to inform managerial decisions
Gain hands-on knowledge of Python coding and its libraries to develop data analytics solutions for your organization's needs.
Derive relationship between two or more variables through regression
Classify data to identify the best possible outcome in a given business context
Define customer segments through cluster analysis
Create a predictive model of customer choice through collaborative filtering
Learn to analyze customer perception through unstructured text analytics
Provide comprehensive solution to any business challenge through better data-driven decision

Who is Business Analytics Python Training for?

Developers
Aspiring Data Scientists,
Managers who want to leverage the flexibility of Python language to create comprehensive analytics solutions for their organizatio

What are the prerequisites for Business Analytics Python Training?

Required

Basic knowledge of any object-oriented programming language
Comfortable with enterprise data and statistical terms

Suggested

Fundamental understanding of Python and libraries such as NumPy, Pandas, SciPy
Basic Statistics and Business Analytics Concepts

Available Training Modes

Live Online Training

12 Hours

Classroom Training

2 Days

Course Outline Expand All

Expand All

Introduction to Business Analytics

Understanding Data

Introduction to Data Analytics

Introduction to Business Analytics, Business Intelligence and Data Mining

Analytical Decision Making

Future of Business Analytics

Big Data Analytics

Social Media Analytics

Basic Statistical Concepts

Type of Data

Sampling Techniques

Applications in industry domains

Methodologies

Decision making using data

Installing Python

Installing Python

Choosing an IDE

iPython/Jupyter Notebook

Data Preprocessing

Inspection of data

Data sanitization

Data manipulation

Reading and Writing Text Files

JSON with Python

HTML with Python

Microsoft Excel files with Pytho

Jump-start Programming with Python

Importing & Reading data

Variable Types

Variable Assignment

Calculation with Variables

Python Lists

Writing functions

Arguments

Methods & String Methods

List Methods

Working with Packages

Selective Import

Control statements

Loops

String operations

Introduction to Pandas

Series

DataFrames

Index objects

Reindex

Drop Entry

Selecting Entries

Data Alignment

Rank and Sort

Summary Statistics

Missing Data

Index Hierarchy

Data Operations

Merge

Merge on Index

Concatenate

Combining DataFrames

Reshaping

Pivoting

Duplicates in DataFrames

Mapping

Replace

Rename Index

Binning

Outliers

Permutatio

Basic Statistics

Measures of central tendency and dispersion

Basic probability

Binomial distribution

Poisson distribution

Normal distribution

Level of significance

P value

Types of errors

Hypothesis Testing

T-Tests

ANOVA

Categorical Data Analysis

Correlation & Covariance

Exploratory Data Analysis (EDA) & Visualization

Installing Seaborn

Basics - Column, Line, Pie Charts

Histogram

Boxplot

Stem & Leaf

Scatterplot

Regression Plot

Heatmaps

Supervised Learning

Regression - Linear Regression

Regression - Multiple Linear Regression

Regression - Logistic Regression

Classification - Decision tree

Time Series Analysis

Case study: Application to supervised learning

Unsupervised Learning

K-means Clustering

Casestudy: Application of unsupervised learning

Recommender System

Collaborative Filtering

Association Rules

Apriori

Case study: Movie/Book recommendatio

Text Analytics

Sentiment Analytics

Lab Session

Case study: Customer segmentation

Case study: Market basket analysis

Who is the instructor for this training?

The trainer for this Business Analytics with Python Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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