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Data Analyst Course:

Objective:
>Understanding Python Programming & Data Analysis Process
>Working on transforming and modeling data .
Who can attend?
>Freshers seeking career in Python/Data Analytics.
>Proffessions with Programming background.
>Working/experienced who want to explore on Data.

Complete Syllabus:
MODULE 1: PYTHON BASICS
Introduction to Python
Variables, keywords and Data types
Operators 
Control Statements
Lists
Tuple
Sets
Dictionary
Functions
Strings
Arrays
 

MODULE 2: PYTHON ADVANCED
Modules and Packages
Exception Handling
File Handling
Object Oriented Programming
Multi-Threading
Regular Expressions
GUI Programming-tkinter

MODULE 3:SQL
Introduction to Database
SQL Architecture
SQL Commands
Storage Classes
Data Types
Create Table
Operators
SQL Clauses
Adding Constraints
Joining Tables
Table Relations
Sub Queries

MODULE 4: DATA ANALYTICS
CH1: Learning NumPy
NumPy basics
Shape manipulation
Copies and Views
Broadcasting rules
Indexing with array of indices
Indexing with boolean array
Indexing with strings
Linear algebra operations
Numpy benefits with matplotlib
CH2: Pandas
Series and Dataframes
Creating dataframes from csv
Plotting csv data
Adding/deleting coulmns with index
Stack/Unstack/Transpose functions
Filtering & Sorting
Grouping
Ways to calculate outliers
Exporting data to txt/csv/excel
Visualization with matplotlib
CH3: Matplotlib & seaborn
Basics of graph plotting
Line plot
Scatter plot
Bar graph
Histogram
Contour plot
Pie chart
Grids
Text plot
Multi plot
3D plotting

MODULE 5: Power BI
basics of Power BI
Stages of business intelligence (BI)
BI Tools
Power BI Components
Architecture of Power BI
Data Sources in Power BI
Data Transformation-Shaping
Working with Parameters
Merge Query
Append Query
Aggregation of data
Duplicate and Reference Tables
Pivot and Un-Pivot of data
Sorting of Data