• Data Types
• Measure Of Central Tendency
• Measures of Dispersion
• Graphical Techniques
• Skewness & Kurtosis
• Box Plot
• Random Variable
• Probability
• Probability Distribution
• Normal Distribution
• SND
• Expected Value
• Sampling Funnel
• Sampling Variation
• Central Limit Theorem
• Confidence Interval

• Introduction to Hypothesis Testing
• Hypothesis Testing (2 proportion test, 2 sample t-test)
• Anova and Chi Square

• Principles of Regression
• Intro to Simple Linear Regression
• Multiple Linear Regression
• Logistic Regression

• Data Cleaning
• Imputation Techniques
• Data Analysis and Visualization
• Scatter Diagram
• Correlation Analysis
• Transformations
• Encoding Methods - OHE, Label Encoders
• Outlier Detection - Isolation Forest
• Calculating the Predictive Power Score (PPS)

• Clustering Introduction
• Hierarchical Clustering
• K Means
• DBSCAN
• PCA
• Association Rules
• Recommender System
• Python Model Deployment

• Regression Tasks / Classification Tasks
• Decision Tree
• KNN
• Support Vector Machines
• Feature Engineering (Tree based methods, RFE, PCA)
• Model Validation Methods (train-test, CV, Shuffle CV, and Accuracy methods)
• Lasso and Ridge Regressions

• ANN
• Optimization Algorithm (Gradient Descent)
• Stochastic Gradient Descent (Intro)
• Back Propagation Method
• Introduction to CNN

• Bagging and Random Forest
• Boosting
• XGBM
• LGBM

• Introduction to Text Mining
• VSM (Vector Space Model)
• Intro to Word Embeddings
• Word Clouds and Document Similarity using Cosine Similarity
• Named Entity Recognition
• Text Classification using Naive Bayes
• Emotion Mining

• Introduction to Time Series
• Level
• Trend and Seasonality
• Strategy
• Scatter Plot
• Lag Plot
• ACF (AutoCorrelation Function)
• Principles of Visualization
• Naive Forecasts
• Forecasting Error and its Metrics
• Model Based Approaches
• AR Model for Errors
• Data Driven Approaches
• MA (Moving Average)
• Exponential Smoothing
• ARIMA

• Python Introduction- Programing Cycle of Python,PythonIDE and Jupyter Notebook

• Variables
• DataType

• Github
• HackerRank
• CodeWars
• Sanfoundry Account Creation Number
• String
• List
• Tuple
• Dictionary

• Operator - Arithmetic
• Comparison
• Decision Making - Loops
• While Loop
• For Loop and Nested Loop
• Number Type Conversion - int(), long(), float()
• Strings - Escape Characters
• String Special Operator
• String Formatting Operator

• Python List
  • Accessing values in list
  • Delete list elements
  • Indexing, Slicing & Matrices
• Tuples
  • Accessing values in Tuples
  • Delete Tuples elements
  • Indexing
  • Slicing & Matrices
• Dictionary
  • Accessing Values from Dictionary
  • Deleting and Updating Elements in Dict
  • Properties of Dictionary
  • Built-In Dictionary Functions & Methods
  • Dict Comprehension

• Function
  • Define Function
  • Calling Function
  • Pass by Reference as Value
  • Function Arguments
  • Anonymous Functions
  • Return Statements
• Scope of Variables
  • Local & Global
  • Decorators and Recursion
  • Import Statements
• Locating Modules
  • Current Directory
  • Python Path
  • Dir() Function
  • Global and Location Functions & Reload() Functions
  • Sys Module and Subprocess Module
  • Packages in Python

• Files in Python
  • Reading Keyboard Input
  • Input Function
  • Opening and Closing Files
  • Syntax and List of Modes
  • Files Object Attribute Open, Close
  • Reading and Writing Files
  • File Position Directories Mkdir Method
  • Chdir() Method
  • Getcwd Method
  • Rmdir

• Exception Handling
  • List of Exceptions
  • Try and Except

• OOP Concepts, Class, Objects, Inheritance, Overriding Methods like __init__, Overloading Operators, Data Hiding

• Match Function
• Search Function
• Matching Vs Searching
• Regular Exp Modifiers and Patterns

• Database Connectivity
• Methods
  • MySQL
  • Oracle
  • How to Install MySQL
  • DB Connection

• What is Tableau?
• What is Data Visualization?
• Tableau Products
• Tableau Desktop Variations
• Tableau File Extensions
• Data Types
• Dimensions
• Measures
• Aggregation Concept
• Tableau Desktop Installation
• Data Source Overview
• Live Vs Extract

• Bar Chart
• Pie Chart
• Heat Maps
• Histogram
• Maps
• Scatterplot
• Donut Chart
• Waterfall Chart
• Dual Axis
• Blended Axis

• Dimension Filter
• Measure Filter
• Data Source Filter
• Extract Filter
• Context Filter
• Quick Filter
• Basic Calculations
• Table Calculations
• Quick Table Calculations
• LOD's (Level of Detail Expressions)
• KPI's (Key Performance Indicators)

• Joins
• Relationship
• Data Blending
• Union

• Hierarchy
• Group
• Sets
• Parameters

• Reference Lines
• Trend Line
• Forecasting
• Clustering
• Dashboard Objects
• Dashboard Actions
• Tableau Public website

• Introduction to Databases
• Introduction to RDBMS (Relational Database Management System)
• Different Types of RDBMS
• Software Installation (MySQL Workbench)

• Data Definition Language
• Data Manipulation Language
• Data Query Language
• Transactional Control Language
• Data Control Language

• SELECT
• LIMIT
• DISTINCT
• WHERE
• AND
• OR
• IN
• NOT IN
• BETWEEN
• EXISTS
• IS NULL
• IS NOT NULL
• WILD CARDS
• ORDER BY
• GROUP BY
• HAVING

• COUNT
• SUM
• AVG
• MIN
• MAX
• COUNT (again)
• String Functions
• Date & Time Functions

• NOT NULL
• UNIQUE
• CHECK
• DEFAULT
• ENUM
• Primary Key
• Foreign Key (Column Level)
• Foreign Key (Table Level)

• Inner Join
• Left Join
• Right Join
• Cross Join
• Self Join
• Full Outer Join

• Index
• View
• Sub-query
• Window Functions
• Stored Procedures
• Exception Handling
• Loops
• Cursor
• Triggers

Module 35 - Introduction ToNeural Network & DeepLearning

• Introduction
• Deep Learning Importance (Strength & Limitation)
• SP | MLP Neural Network Overview
• Neural Network Representation
• Activation Function
• Loss Function
• Importance of Non-Linear Activation Function
• Gradient Descent for Neural Network

• Train
• Test & Validation Set
• Vanishing & Exploding Gradient
• Dropout Regularization
• Optimization Algorithms
• Learning Rate
• Tuning
• Softmax

• CNN (Convolutional Neural Network)
• Deep Convolution Model
• Detection Algorithm
• CNN Face Recognition

• RNN (Recurrent Neural Network)
• LSTM (Long Short-Term Memory)
• BiDirectional LSTM (Bidirectional Long Short-Term Memory)

• Introduction to BigData, Challenges in Big Data and Workarounds| Introduction to Hadoop and Its Components|HadoopComponents andHands-On|Understand the Map Reduce and ItsDrawbacks

• Introduction to Spark and DataBricks|Spark Components, Spark MLlib Spark &DataBricks andHands-On One ML Model in Spark

• Cloud Computing
• Azure Cloud Platform
• Cloud Applications
• Cloud Services
• Open AI Studio

• Data Structures & Operators in R|Conditional Statement|Decision Making|Loops|Strings|Functions|How to Import Data set in R| Programming Statistical Graphics