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Full programme

Data Science

From statistics and feature engineering through machine learning, SQL and the reporting tools teams actually run — every track, module and topic below.

7Tracks
22Modules
160Topics
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What the programme covers

Seven tracks. Pick one to jump straight to it, then open a module to see every topic.

Data Science Primer and Statistics29 Machine Learning33 Data Visualization and Story Telling10 SQL38 Excel19 Tableau15 Power BI16
01

Data Science Primer and Statistics

4 modules · 29 topics
01 Basics of Data Science 7 topics
  • What is Data Science?
  • What does Data Science involve?
  • Era of Data Science
  • Business Intelligence vs Data Science
  • Life cycle of Data Science
  • Tools of Data Science
  • Application of Data Science
02 Feature Engineering 5 topics
  • What is Feature
  • Feature Engineering
  • Feature Engineering Process
  • Benefit
  • Feature Engineering Techniques
03 Exploratory Data Analysis 11 topics
  • Introduction
  • Stages of Analytics
  • CRISP DM Data Life Cycle
  • Data Types
  • Introduction to EDA
  • Exploratory Data Analysis
  • First Business Moment Decision
  • Second Business Moment Decision
  • Third Business Moment Decision
  • Correlation
  • Fourth Business Moment Decision
04 Inferential Statistics & Hypothesis Testing 6 topics
  • Basics Of Probability
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Central Limit Theorem
  • Concepts Of Hypothesis Testing - I: Null And Alternate Hypothesis, Making A Decision, And Critical Value Method
  • Concepts Of Hypothesis Testing - II:P-Value Method And Types Of Errors Industry Demonstration Of Hypothesis Testing: Two-Sample Mean And Proportion Test, A/B Testing
02

Machine Learning

6 modules · 33 topics
01 Linear Regression 5 topics
  • Simple Linear Regression
  • Simple Linear Regression In Python
  • Multiple Linear Regression
  • Multiple Linear Regression In Python
  • Industry Relevance Of Linear Regression
02 KNN classifier 4 topics
  • Data mining classifier technique
  • Application of KNN classifier
  • Lazy learner classifier
  • Altering hyperparameter(k) for better accuracy
03 Logistic Regression 5 topics
  • Univariate Logistic Regression
  • Multivariate Logistic Regression: Model
  • Building And Evaluation
  • Logistic Regression:
  • Industry Applications
04 Decision Tree Classifier 7 topics
  • Rule based classification method
  • Different nodes for develop decision trees
  • Discretization
  • Entropy
  • Decision Tree Classifier
  • Greedy approach
  • Information gain
05 Support Vector classifier 4 topics
  • Black box
  • SVM hyperplane
  • Max margin hyperplane
  • Kernel tricks for non linear spaces
06 Ensemble Learning 8 topics
  • Challenges with standalone model
  • Reliability and performance of a standalone model
  • Homogeneous & Heterogeneous Ensemble Technique
  • Bagging & Boosting
  • Ensemble Learning
  • Random forest
  • Stacking
  • Voting & Averaging technique
03

Data Visualization and Story Telling

3 modules · 10 topics
01 Basic Visualization Tools 4 topics
  • Bar Charts
  • Histograms
  • Pie Charts
  • Box Plots
02 Specialized Visualization Tools 4 topics
  • Pair plot
  • Word Clouds
  • Radar Charts
  • Waffle Charts
03 Basic Visualization Tools Continued 2 topics
  • Scatter Plots
  • Line Plots and Regression
04

SQL

5 modules · 38 topics
01 Getting Started and Creating, Selecting & Retrieving Data with SQL 11 topics
  • Introduction to Databases
  • How to create a Database instance on Cloud?
  • Provision a Cloud hosted Database instance.
  • What is SQL?
  • Thinking About Your Data
  • Relational vs. Transactional Models ER Diagram
  • CREATE Table Statement and DROP tables
  • UPDATE and DELETE Statements
  • Retrieving Data with a SELECT Statement
  • Creating Temporary Tables
  • Adding Comments to SQL
02 Subqueries and Joins in SQL 8 topics
  • Using Subqueries
  • Subquery Best Practices and Considerations
  • Joining Tables
  • Cartesian (Cross) Joins
  • Inner Joins
  • Aliases and Self Joins
  • Advanced Joins: Left, Right, and Full Outer Joins
  • Unions
03 Modifying and Analyzing Data with SQL 5 topics
  • Working with Text Strings
  • Working with Date and Time Strings
  • Date and Time Strings Examples
  • Case Statements
  • Views
04 Filtering, Sorting, and Calculating Data with SQL 7 topics
  • Basics of Filtering with SQL
  • Advanced Filtering: IN, OR, and NOT
  • Using Wildcards in SQL
  • Sorting with ORDER BY
  • Math Operations
  • Aggregate Functions
  • Grouping Data with SQL
05 Accessing Databases using Python 7 topics
  • How to access databases using Python?
  • Writing code using DB-API
  • Connecting to a database using DB API
  • Create Database Credentials
  • Connecting to a database instance
  • Creating tables, loading, inserting, data and querying data
  • Analysing data with Python
05

Excel

1 modules · 19 topics
01 Analyzing and Visualizing Data using Excel 19 topics
  • Input data & handling large spreadsheets
  • Tricks to get your work done faster
  • Automating data analysis (Excel VLOOKUP,IF Function, ROUND and more)
  • Transforming messy data into shape
  • Cleaning, Processing and Organizing large data
  • Spreadsheet design principles
  • Drop-down lists in Excel and adding data validation to the cells.
  • Creating Charts & Interactive reports with Excel Pivot Tables, Pivot Charts, Slicers and Timelines
  • Functions like: - COUNTIFS, COUNT, SUMIFS, AVERAGE and many more.
  • Excel features: - Sort, Filter, Search & Replace Go to Special etc...
  • Importing and Transforming data (with Power Query)
  • Customize the Microsoft Excel interface
  • Formatting correctly for professional reports.
  • Commenting on cells.
  • Automate data entry with Autofill and Flash-fill.
  • Writing Excel formulas & referencing to other workbooks / worksheets.
  • Printing options
  • Charts beyond column and bar charts:- Pareto chart, Histogram, Tree map, Sunburst
  • Charts & more
06

Tableau

1 modules · 15 topics
01 Analyzing and Visualizing Data using Tableau 15 topics
  • Introduction to Data Visualization
  • Tableau Introduction and Tableau Architecture
  • Exploring Data using Tableau
  • Working with Data using Tableau including Data Extraction and Blending
  • Various Charts in Tableau(Basics to Advanced)
  • Sorting-Quick Sort, Sort from Axis, Legends, Axis, Sort by Fields
  • Filtering- Dimension Filters, Measure Filters,Date Filters, Tableau Context Filters
  • Reference Lines, Bands and Distribution
  • Parameters, Dynamic Parameters and Actions
  • Forecasting-Exponential Smoothening Techniques
  • Clustering
  • Calculated Fields in Tableau, Quick Tables
  • Tableau Mapping Features
  • Tableau Dashboards, Dashboards Action and Stories
  • Groups , Sets and Combined Sets
07

Power BI

2 modules · 16 topics
01 Introduction To Power BI 9 topics
  • Introduction to Power BI – Need, Imprtance
  • Power BI – Advantages and Scalable Options
  • Power BI Data Source Library and DW Files
  • Business Analyst Tools, MS Cloud Tools
  • Power BI Installation
  • Power BI Desktop – Instalation, Usage
  • Sample Reports and Visualization Controls
  • Understanding Desktop & Mobile Editions
  • Report Rendering Options and End User Access
02 Creating POWER BI Reports, Auto Filters 7 topics
  • Report Design with Databse Tables
  • Report Visuals, Fields and UI Options
  • Reports with Multiple Pages and Advantages
  • Pages with Multiple Visualizations. Data Access
  • "GET DATA" Options and Report Fields, Filters
  • Report View Options: Full, Fit Page, Width Scale
  • Report Design using Databases & Queries

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