Advanced Data Analytics Certification - United Kingdom

Advanced Data Analytics Certification​ Course Outline

Domain 1: Data Analytics

Module 1: Introduction to Data Analytics

• Data Analytics Overview
• Types of Data Analytics
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
• Benefits of Data Analytics
• Data Visualisation for Decision Making 
• Data Types, Measure of Central Tendency, Measures of Dispersion
• Graphical Techniques, Skewness and Kurtosis, Box Plot
• Descriptive Stats
• Sampling Variation, Central Limit Theorem, Confidence Interval
• Optimisation Techniques for Data Analytics

Module 2: Introduction to Statistical Analysis

• Counting, Probability, and Probability Distributions
• Sampling Distributions
• Estimation and Hypothesis Testing
• Scatter Diagram
• ANOVA and Chi-Square
• Imputation Techniques
• Data Cleaning
• Correlation and Regression

Module 3: Data Wrangling with SQL

• Introduction to SQL
• Database Normalisation
• Entity-Relationship Model
• SQL Operators
• Join, Tables, and Variables
• SQL Functions
• Subqueries
• Views and Stored Procedures
• User-Defined Functions
• SQL Performance and Optimisation
• Advanced Concepts
  • Correlated Subquery
  • Grouping Sets

Module 4: Presto

• Introduction to Presto
• Writing Queries in Presto on Large Data Sets

Module 5: Feature Engineering

• Handling Unstructured Data
• Machine Learning Algorithms
• Bias Variance Trade-Off
• Imbalance Data
• Handling Unbalanced Data
• Boosting
• Model Validation
• Hyper Parameter Optimisation
• Advanced Machine Learning Libraries – Xgboost
• Solving Problems on Kaggle

Domain 2: Business Analytics with Excel

Module 6: Introduction to Data Analysis with MS Excel

• Steps to Analyse Data
• Introduction to Tables

Module 7: Cleaning Data with Text Functions

• Removing Unwanted Characters from the Text
  • Steps for Data Cleaning

Module 8: Sorting and Filtering

• What is Sorting and Filtering?
• Applying Sorting on Two Columns
• Steps to Sort Dates and Columns by Colours
• Apply Filtering
• Clear Filter
• Apply Filter on Text

Module 9: Exploring Lookup Functions

• VLookUp Functions in Excel
• HLookUp Functions in Excel

Module 10: Introduction to Power Pivot and Formula Auditing

• Working with Pivot Tables
• How to Use Power Pivot?
• Measures
• Dimension Tables
• Relationships
• Advanced Functions
• Data Visualisation and Analysis
• Show Formulas
• Trace Precedents
• Trace Dependents
• Evaluate Formula

Module 11: DAX Variables and Formatting

• What is DAX?
• Data Types and Operators
• DAX Variables
• Formatting DAX Code
• Debugging Errors in DAX Code
• Progressive DAX Syntax and Functions

Module 12: Introduction to Power Map

• Create a Power Map
• Explore Sample Datasets in Power Map
• Visualise Data in Power Map
• Create a Custom Map in Power Map

Module 13: Design a Dashboard Using Data Model

• Using PowerPoint and Excel
• Make a Dashboard in Excel
• Customise with Macros, Colour, etc.
• Make a Dashboard in Smartsheet

Domain 3: Programming Basics and Data Analytics with Python

Module 14: Python for Data Analysis - NumPy

• Introduction to NumPy
• NumPy Arrays
• Aggregations
• Computation on Arrays: Broadcasting
• Comparison, Boolean Logic and Masks
• Fancy Indexing
• Sorting Arrays
• NumPy’s Structured Arrays

Module 15: Python for Data Analysis – Pandas

• Installing Pandas
• Pandas Objects
• Data Indexing and Selection
• Operating on Data in Pandas
• Handling Missing Data
• Hierarchical Indexing
• Concat and Append
• Merge and Join
• Aggregations and Grouping
• Pivot Tables
• Vectorised String Operations
• Working with Time Series

Module 16: Python for Data Visualisation – Matplotlib

• Overview
• Object-Oriented Interface
• Simple Line Plots and Scatter Plots
• Visualising Errors
• Contour Plots
• Histograms, Binnings, and Density
• Customising Plot Legends
• Customising Colour Bars
• Multiple Subplots
• Text Annotation
• Three-Dimensional Plotting

Module 17: Python for Data Visualisation – Seaborn

• Installing Seaborn and Load Dataset
• Plot the Distribution
• Regression Analysis
• Basic Aesthetic Themes and Styles
• Distinguish Between Scatter Plots, Hexbin Plots, and KDE Plots
• Use Boxplots and Violin Plots

Domain 4: Tableau Training

Module 18: Get Started

• What is Tableau?
• Steps in Creating Tableau Data Analysis Report
• Navigation
• Data Terminology
• Design Flow
• File Types
• Data Types
• Show Me

Module 19: Data Sources

• Types of Data Sources
• Custom Data View
• Extracting Data
• Fields Operations
• Editing Metadata
• Data Joining
• Data Blending

Module 20: Worksheets

• Add and Rename
• Save and Delete
• Reorder Worksheet
• Paged Workbook

Module 21: Calculations

• Operators
• Functions
• Calculations
  • Numeric
  • String
  • Date
  • Table
• LOD Expressions

Module 22: Sort and Filters

• Basic Sorting
• Basic Filters
• Filters
  • Quick
  • Context
  • Condition
• Top Filters
• Filter Operations

Module 23: Tableau Charts

• Chart
  • Bar
  • Line
  • Pie
• Crosstab
• Scatter Plot
• Bubble Chart
• Bullet Graph
• Box Plot
• Tree Map
• Bump Chart
• Gantt Chart
• Histogram
• Motion Charts
• Waterfall Charts