Certificate Program in Data Science & Advanced Machine Learning using R & Python

Learn concepts of data analytics, data science and advanced machine learning using R and Python with hands-on case studies

Certificate Program in Data Science & Advanced Machine Learning using R & Python

Course Description

This is a comprehensive Imurgence course using R and Python which dives deep into data analytics, R interface, data handling by thoroughly understanding data structure and data types in R, R internal functions, data with manipulation and visualisation, basic statistics, probability, inferential, linear and logistic regression, decision tree, ensemble learning, support vector machines, market basket analysis, k-nearest neighbours, clustering, artificial neural network, introduction to data analytics, Python IDE, Python basics, Python packages, and linear and logistic regression.

Course Outcomes:
  • Upon successful completion of this course, the learner will be skilled in data science and machine learning using R and Python for predictive analytics on data and use machine learning to solve problems.
Course Details:

Target Audience

This course is ideal for anyone looking to improve their skills or start a career in data science, business analytics, artificial intelligence (AI) or machine learning.

Access Timeframe

Three months from the date of access.

Prerequisites

There are no prerequisites for this course, but a general understanding of statistics and an inclination to learn coding would benefit the learner.
Certificate Info:

Type of Certification

Certificate of Completion

Format of Certification

Digital

Professional Association/Affiliation

The certificate is issued by Imurgence an autonomous institution.

Method of Obtaining Certification

Upon successful completion of this course, the learner will be sent a digital copy of the certificate to their email.

Course Outline

In this module, you will learn the following:
  • Overview Analytics
  • Application of Analytics
In this module, you will learn the following:
  • Installation of R Base
  • Installation of R Studio
  • How to Use R Studio
In this module, you will learn the following:
  • Data Structures
  • Data Types
  • Basic Operations in R
In this module, you will learn the following:
  • Decision Making
  • Loops
In this module, you will learn the following:
  • Built-in Functions
  • User Defined Functions
In this module, you will learn the following:
  • Import and Export of Data
  • Subsetting
  • Merge and Concatenate
In this module, you will learn the following:
  • Basic Plots
In this module, you will learn the following:
  • Descriptive Statistics
In this module, you will learn the following:
  • Basic Definitions
  • Basic Rules for Probability
  • Baye's Theorem
In this module, you will learn the following:
  • Hypothesis
  • Hypothesis Testing
  • Correlation
In this module, you will learn the following:
  • Simple Linear Regression
  • Multiple Linear Regression
  • Regularization
In this module, you will learn the following:
  • Basics
  • Logistic Regression Theory
  • Implementation in R
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Introduction
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Why Visualisation? Why Tableau? Things you should know about Tableau
In this module, you will learn the following:
  • Connecting to Data and Introduction to Data Source Concepts
  • Understanding the Tableau Workspace
  • Dimensions and Measures
  • Tour of Shelves
  • Building Basic Views
  • Help Menu
  • Saving and Sharing Your work
  • Concepts and Options When Connecting to Data
In this module, you will learn the following:
  • Joining Multiple Tables
  • Copy and Paste
  • Data Extracts
In this module, you will learn the following:
  • Understand how to deal with data changes in your data source such as field addition, deletion or name change
  • Re-using and sharing data connections - the same concept of meta data
  • Working with multiple connections in the same workbook analysis
In this module, you will learn the following:
  • Marks
  • Size and Transparency
  • Highlighting
  • Working with Dates
  • Dual Axis/Multiple Measures
  • Combo Charts with Different Mark Types
  • Geographic Map
  • Heat Map
  • Scatter Plots
  • Pie Charts and Bar Charts
  • Small Multiples
  • Working with Aggregate Versus Disaggregate Data
In this module, you will learn the following:
  • Sorting and Grouping
  • Aliases
  • Filtering and Quick Filters
  • Totals and Subtotals
  • Aggregation and Disaggregation
  • Percent of Total
  • Working with Statistics and Trendlines
In this module, you will learn the following:
  • Working with String Functions
  • Basic Arithmetic Calculations
  • Date Math
  • Working with Totals
  • Custom Aggregations
  • Logic Statements
In this module, you will learn the following:
  • Options in Formatting Your Visualisation
  • Working with Labels and Annotations
  • Effective Use of Titles and Captions
  • Introduction to Visual Best Practices
In this module, you will learn the following:
  • Theory
  • Understanding the Buying Pattern of a Customer
In this module, you will learn the following:
  • Downloading Shapes from the Internet
  • Making Use of Customized Shapes
In this module, you will learn the following:
  • Combining Multiple Visualisations into a Dashboard
  • Making Your Worksheet Interactive by Using Actions and Filters
  • An Introduction to Best Practices in Visualisation
In this module, you will learn the following:
  • Publish to Reader
  • Packaged Workbooks
  • Publish to Office
  • Publish to PDF
  • Publish to Tableau Server and Sharing over the Web
In this module, you will learn the following:
  • Overview of Analytics
  • Application of Analytics
In this module, you will learn the following:
  • Installation of Python
  • How to Use Python
In this module, you will learn the following:
  • Data Types and Data Structure
  • Basic Operations in Python
  • Functions
In this module, you will learn the following:
  • Pandas
  • Numpy
  • Scikit-learn
  • Matplotlib
In this module, you will learn the following:
  • Descriptive Statistics
In this module, you will learn the following:
  • Simple Linear Regression
  • Multiple Linear Regression
  • Regularization
In this module, you will learn the following:
  • Basics
  • Logistic Regression Theory
  • Implementation in Python
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Introduction
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Theory
  • Practical
In this module, you will learn the following:
  • Why Visualisation? Why Tableau? Things you should know about Tableau
In this module, you will learn the following:
  • Connecting to Data and Introduction to Data Source Concepts
  • Understanding the Tableau Workspace
  • Dimensions and Measures
  • Tour of Shelves
  • Building Basic Views
  • Help Menu
  • Saving and Sharing Your work
  • Concepts and Options When Connecting to Data
In this module, you will learn the following:
  • Joining Multiple Tables
  • Copy and Paste
  • Data Extracts
In this module, you will learn the following:
  • Understand how to deal with data changes in your data source such as field addition, deletion or name change
  • Re-using and sharing data connections - the same concept of meta data
  • Working with multiple connections in the same workbook analysis
In this module, you will learn the following:
  • Marks
  • Size and Transparency
  • Highlighting
  • Working with Dates
  • Dual Axis/Multiple Measures
  • Combo Charts with Different Mark Types
  • Geographic Map
  • Heat Map
  • Scatter Plots
  • Pie Charts and Bar Charts
  • Small Multiples
  • Working with Aggregate Versus Disaggregate Data
In this module, you will learn the following:
  • Sorting and Grouping
  • Aliases
  • Filtering and Quick Filters
  • Totals and Subtotals
  • Aggregation and Disaggregation
  • Percent of Total
  • Working with Statistics and Trendlines
In this module, you will learn the following:
  • Working with String Functions
  • Basic Arithmetic Calculations
  • Date Math
  • Working with Totals
  • Custom Aggregations
  • Logic Statements
In this module, you will learn the following:
  • Options in Formatting Your Visualisation
  • Working with Labels and Annotations
  • Effective Use of Titles and Captions
  • Introduction to Visual Best Practices
In this module, you will learn the following:
  • Theory
  • Understanding the Buying Pattern of a Customer
In this module, you will learn the following:
  • Downloading Shapes from the Internet
  • Making Use of Customized Shapes
In this module, you will learn the following:
  • Combining Multiple Visualisations into a Dashboard
  • Making Your Worksheet Interactive by Using Actions and Filters
  • An Introduction to Best Practices in Visualisation
In this module, you will learn the following:
  • Publish to Reader
  • Packaged Workbooks
  • Publish to Office
  • Publish to PDF
  • Publish to Tableau Server and Sharing over the Web

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