Data Science
Module 1
1) INTRODUCTION
- Data Science Road Map
- Why Data Science
- Future of Data Science
- Artificial Intelligence
- Machine Learning
- Deep Learning
- History
2) DATA WRANGLING
- What is Data Wrangling
- Life Cycle of Data Wrangling
- Types of Data Gathering
- Data Wrangling components
3)DATA MINING
- What is Data Mining
- Data Mining Architecture
- Types of Data Mining
- Real Time Analysis of Data Mining
4)DATA CLEANSING
- What is Data Cleansing
- Life cycle of Data Cleansing
- Data Cleansing Component
- Different Types of Data Cleaning
5)DATA SCIENCE
- What is Data Science
- Data Science life cycle
- Why Data Scientists are in demand
- What is a Data Product?
- The growing need for Data Science
- Large Scale Analysis Cost vs Storage
- Data Science Skills
PYTHON PROGRAMMING
Module 1
PYTHON BASIC
- Introduction to Python
- History of Python
- Python Installation
- IDE’s – Pycharm
- Identifiers
- Statements
- Comments
- Variables
- Memory Management
- Types of Data Types
- Integers
- Float
- Complex
- Boolean
- String
- Operators
- Arithmetic
- Relational
- Logica
- Assignment
- Bitwise
CORE PYTHON
- Conditional Statements
- Iterative Statements
- Interruptive Statements
- List
- Tuple
- Set
- Dictionary
- Functions
- Arguments Type
- Nested Function
- Closure Property
- Recursion
- Files
- Text Files
- CSV Files
- PDF Files
ADVANCE PYTHON
- OOPS
- Inheritance
- Polymorphism
- Encapsulation
- Abstraction
- Lambda Function
- Map, Filter, Reduce
- Regular Expression
- Exception Handling
- Nested Function
- Serialization
- REST API
- GIT / GIT HUB
PYTHON PROGRAMMING
Module 2
NUMPY
- What is Numpy
- History of Numpy
- What is Ndarray
- Creating Numpy Array
- Array Function
- Creating Numpy Array
- Numerical
- Homogenous
- Diagonal
- Random Numbers
- Array Attributes
- Creating Multi-Dimensional Array
- Extracting Data from Arrays
- Using Indexing
- Using Slicing
- Boolean Indexing
- Random Indexing
- Resizing & Reshaping
- Transpose
- Vector multiplication
- Array Attributes
- Array Operations
- Broadcasting Rules
PANDAS
- What is Data Manipulation
- What is Pandas
- History of Pandas
- What is Data Structure
- Pandas Data Structure
- Series
- DataFrame
- Creating Series
- Creating DataFrame…
- Extracting Data
- Manipulation of Data
- Inserting Columns & Rows
- Changing Columns & Rows
- Deleting column / rows
- Re-indexing Options
- Customization
- Indexing & Selecting
- Date Functionality
- Identifying Outlier
- Replace NaN using Fillna,
- Interpolate Deleting using Drop, Dropna
- Concatenate and Merge
- Groupby, Pivot Table and Cross Tab
DATABASE
Module 1
DATABASES
- What is Database?
- Types of Databases?
- What is DBMS?
- What is RDBMS?
- History of RDBMS
SQL Server / MySql
- CRUD Operation
- Select … Where
- Insert
- Update
- Delete
- Joins
- Primary & Foreign Keys Connectivity with Python
MONGODB
- What is NoSQL DB
- NoSQL DB and SQL DB
- History MongoDB
- Features NoSQL Databases
- Create & Drop Database
- Create & Drop Collection
- Data Types
- Create, Insert, Update, Delete
- Query Document
STATISTICS
Module 2
STATISTICS
- What is Statistics
- Types of Statistics
- What is Population
- What is Sample
- Different Sampling Techniques
- Statistics Terminology
DESCRIPTIVE STATISTICS
- Central Tendency Measure
- Measure of Variability
- Dispersion Measures
- Data Distributions
INFERENTIAL STATISTICS
- Hypothesis
- What is Sample Types of Hypothesis
- Null Hypothesis
- Alternative Hypothesis
- Chi-Square Test
- Anova Test
- T-Test
- Z-Test
FEATURE ENGINEERING
Module 2
OUTLIER DETECTION
- Standard Deviation Method
- Inter Quartile Range Method
- Z-Score Method
- Percentile Method
FEATURE SCALING
- Standardization
- Normalization
IMPUTATION TECHNIQUES
- Simple Impute
- Fillna
- Interpolate
EXPORATORY DATA ANALYSIS
- Uni - Variate Analysis
- Bi – Variate Analysis
- Multi – Variate Analysis
- Matplotlib
- Seaborn
ENCODING TECHNIQUES
- Pandas Dummies
- One Hot Encoding
- Label Encoding
- Ordinal Encoding
- Lambda with Apply Function
- Lambda with Map Function
IMBALANCE DATASET
- Under Sampling
- Over Sampling
- SMOTE
- Random Over Sampling
DATA VISUALIZATION
Module 2
MATPLOTLIB
- Bar Graph
- Pie Chart
- Box Plot
- Histogram
- Line Chart
- Subplots
- Scatter Plot
TABLEAU
- What is Tableau
- Tableau Architecture
- Server Components
- Install Tableau
- Types of Filters
- Groups in Tableau
- Tableau Charts
- Tableau Graphs
SEABORN
- Count plot
- Heatmap
- Scatter plot
- Pair plot
- Violin Plot
- Box plot
- Strip Plot
- Swarm Plot