Data Science Primer and Statistics

Basics of Data Science

  • 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

Feature Engineering

  • What is Feature
  • Feature Engineering
  • Feature Engineering Process
  • Benefit
  • Feature Engineering Techniques

Exploratory Data Analysis

  • 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

Inferential Statistics & Hypothesis Testing

  • 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

Machine Learning

Linear Regression

  • Simple Linear Regression
  • Simple Linear Regression In Python
  • Multiple Linear Regression
  • Multiple Linear Regression In Python
  • Industry Relevance Of Linear Regression

KNN classifier

  • Data mining classifier technique
  • Application of KNN classifier
  • Lazy learner classifier
  • Altering hyperparameter(k) for better accuracy

Logistic Regression

  • Univariate Logistic Regression
  • Multivariate Logistic Regression: Model
  • Building And Evaluation
  • Logistic Regression:
  • Industry Applications

Decision Tree Classifier

  • Rule based classification method
  • Different nodes for develop decision trees
  • Discretization
  • Entropy
  • Decision Tree Classifier
  • Greedy approach
  • Information gain

Support Vector classifier

  • Black box
  • SVM hyperplane
  • Max margin hyperplane
  • Kernel tricks for non linear spaces

Ensemble Learning

  • 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

Data Visualization and Story Telling

Basic Visualization Tools

  • Bar Charts
  • Histograms
  • Pie Charts
  • Box Plots

Specialized Visualization Tools

  • Pair plot
  • Word Clouds
  • Radar Charts
  • Waffle Charts

Basic Visualization Tools Continued

  • Scatter Plots
  • Line Plots and Regression

SQL

Getting Started and Creating, Selecting & Retrieving Data with SQL

  • 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

Subqueries and Joins in SQL

  • 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

Modifying and Analyzing Data with SQL

  • Working with Text Strings
  • Working with Date and Time Strings
  • Date and Time Strings Examples
  • Case Statements
  • Views

Filtering, Sorting, and Calculating Data with SQL

  • 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

Accessing Databases using Python

  • 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

Excel

Analyzing and Visualizing Data using Excel

  • 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

Tableau

Analyzing and Visualizing Data using Tableau

  • 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

Power BI

Introduction To Power BI

  • 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

Creating POWER BI Reports, Auto Filters

  • 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