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DATA Analysis

Data Analysis Institute In Pitampura In Delhi

DATA ANALYSIS

Course Syllabus

Module 1: PYTHON PROGRAMMING

Introduction

  • History
  • Features Setting up path
  •  Working with Python Basic Syntax
  • Variable & Data Types
  • Operators (Arithmetic, Relational,
    Membership, Bitwise etc.)
  •  Punctuators, Indentation, Comments

Conditional Statements

  •  If
  •  If- else
  •  If-elif
  •  Nested if-else

Iterative Statements (Looping)

  • For
  • While
  • Loop else statement
  • Nested loops

Control Statements

  • Break
  • Continue
  •  Pass

String Manipulation

  •  Accessing Strings
  •  Basic Operations
  •  String slices
  •  Function and Methods

Lists

  •  Introduction
  •  Creating List
  •  Accessing list
  •  List Operations
  •  Function and Methods
  •  Working with lists (List Programs)

Tuple

  •  Introduction
  •  Accessing Tuples
  •  Operations
  •  Working
  •  Functions and Methods

Dictionaries

  •  Introduction (Key: Values)
  •  Accessing values/elements
  •  Dictionaries Properties
  •  Functions and Methods

Sorting & Searching Concepts

  •  What is Sorting
  •  Bubble Sort
  •  Insertion Sort
  •  Binary Search

Functions

  •  Defining a function
  •  Calling a function
  •  Types of functions
  •  Function Arguments
  •  Scope of Variables
    o Global and local variables
  •  Returning Values from function

Python Libraries/ Packages/ Modules

  •  Python standard libraries
  •  Structure of a module, Importing module
  •  Math module,Random module
  •  Urlib and WebBrowser modules
  •  Packages , Importing Python Libraries
  •  Creating a Python Library/package(s)

Input-Output (File Handling)

  •  Data Files (Text and Binary Files)
  •  Opening/Closing a File
  •  Reading data from File
  •  Writing data in a file from keyboard
  •  Printing on screen
  •  File Handling Functions
  •  Standard Input, Output and Error streams

Exceptional Handling

  •   Exception
  •   Exception Handling Except clause
  •   Try ? Finally clause User Defined Exceptions

Regular Expression

  •  Pattern Matching,
  • Meta Characters for making patterns
  • match(), sub(), findall(), search(), split()method

Module 2:  ADVANCED EXCEL 

  • Workbook, Worksheet, Workspaces
  • Row & Column Settings
  • Calculation Basics in Excel
  • References (Relative, Absolute, Mixed)
  • Find & Replacing Data
  • Header & Footer setting
  • Working with Chart
  • Functions (Financial, Statistical etc.)
  • Formulas (DSUM, DMAX, DMIN, DCOUNT
  • If And Analysis, What if Analysis
  •  Goal Seek, Solver, Scenarios
  •  Naming Cell Range
  •  Protecting sheet & workbook  Autofill, Autocorrect, Autoformat

DATA ANALYSIS IN EXCEL (ADVANCE EXCEL)

  • Importing and Exporting Data
  •  Auditing, Freeze Panes
  •  Grouping and Subtotal
  •  Macro (recording tool)/EDITING
  •  Customizing Sheet/Cells/Rows/Columns
  •  Customizing Excel Window
  •  Sorting and Filtering Data, Advance
    Filter
  •  Data Validation
  •  Pivot Table, Pivot Chart
  •  Consolidation of Sheets
  •  H Lookup, V Lookup
  •  Creating Reports, Marks sheet etc
  •  Loan Sheet Preparation (PPMT, IPMT, PMT)
  •  RD CALCULATION
  •  Printing Worksheet, Custom List
  •  Working with Excel CSV files
  •  Making Excel to PDF file

# LIVE PROJECT WORK 

  •  DATABASE MGMT. SYSTEM (DBMS)
  •  DBMS TERMINOLOGIES
  •  RELATIONAL DATABASE
  •  Introduction to SQL/MySQL
  •  SQL DATA TYPES
  •  INTEGRITY CONSTRAINTS
  •  CREATING TABLES BASED ON INTEGRITY
    CONSTRAINTS
  •  ALTERING TABLE
    •  ADDING NEW FIELDS
    • CHANGING EXISTING FIELDS
  •  INSERT, UPDATE, DELETE
  •  SELECT COMMAND
  •  WHERE (RETRIEVAL OF SPECIFIC ROWS)
  • WORKING WITH EXPRESSIONS
  •  CHECKING MULTIPLE CONDITIONS (AND, OR, NOT OPERATOR)
  •  EXISTS, NOT EXISTS
  •  BETWEEN, NOT BETWEEN ARRANGING RECORD (ORDER
  •  DISTINCT CLAUSE
  •  WORKING WITH NULL VALUES
  •  SQL FUNCTIONS
    • AGGREGATE FUNCTIONS
    • ARITHMETIC FUNCTIONS
    • CHARACTER/STRING FUNCTIONS
    • DATE FUNCTIONS
  •  GROUPING RESULTS (GROUP BY)
  •  PLACING CONDITIONS ON GROUPS (HAVING CLAUSE)
  •  TABLE ALIASES
  •  JOINS
    • MULTI-TABLE JOINS
    • EQUI JOIN
    • CARTESIAN JOIN
    • OUTER JOINS
    • UNIONS IN SQL
  •  INDEXES IN SQL
  •  CUSTOMISING TABLE
    • CREATING TABLE FROM OTHER TABLE
    • CREATING DUPLICATE TABLE
    • RENAMING A TABLE
    • RENAMING AN ATTRIBUTE, GRANT & REVOKE

Module 3: Database (MySQL)

  • BASICS OF ACCOUNTING
  • Ledger Posting, Bill wise details, Cost center, Allow Invoice
  • TDS(Tax deducted at source), TCS(Tax collecting at sources)
  • Debit note and Credit note, Price list, Bill of material
  • Check printing, Zero value entry,
  • Multiple Godown, Integrate account and inventor
  • Budgets and scenario management
  • Maintain stock categories
  • Maintain batch wise details (set expiry dates for batches)
  • Use different actual and billed quantity
  • Separate discount column on invoices
  • Use tracking number (delivery/receipt notes)
  • Use rejection inward/outward notes
  • Payroll (Basic Salary, HRA, TA, DA, PF, ESI, Net Salary)
  • Profit and Loss Statement, Balance Sheet

Module 4: Data Analytics With Python

GETTING STARTED WITH PYTHON LIBRARIES

  •  What is data analysis?
  •  Why python for data analysis?
  •  Essential Python Libraries
  •  Installation on and setup
  •  Ipython
  • Jupyter Notebook

Python Arrays (NumPy)

  • Numpy Arrays , Numpy Data types
  • Numpy Array Indexing
  • Numpy Mathematical Operations
  • Indexing and slicing
  • Stacking arrays, Sorting arrays
  • Numpy Statics related Functions

Python Pandas

  • andas Series
  •  Pandas Dataframes (2-Dimensional)
  •  Data aggregation with pandas
  •  Data Indexing and selection
  •  Operation on Data in Pandas
  •  loc and iloc map
  •  apply,apply_map, group_by
  •  Querying data in pandas
  •  Dealing with dates
  •  Reading and Writing to CSV fi les with pandas
  •  Reading and Writing to SQL with
    pandas
  • Reading and Writing to HTML files
    with panda

Data Visualization Python Matplotlib

  •  Matplotlib Pyplot
  •  Matplotlib Plotting
  •  Matplotlib Markers
  •  Matplotlib Line
  •  Matplotlib Scatter
  •  Matplotlib Bars
  • Matplotlib Pie Charts

Introduction Of Seaborn

  • Categorical Plots, Bar Plots, Box Plots
  • Heatmaps Plots, Pair Plots
  • Regression Plots
  •  Style and Color

Plotly – Python Plotting

  • Introduc on to Plotly – Python Plotting, Plotly

Geographical Plotting

  • Introduction to Geographical plotting
  • Choropleth Maps

Database Connectivity with MySQL

  •  MySQL Operations
  •  Database Connection
  •  Creating New Database
  •  Creating Tables
  •  Inserting Records in Table
  •  Fetching Records from Database
    Using Python
  •  Read Operation using Select, Where,
  •  OrderBy etc
  •  Update Operations
  •  Join Operations
  •  Performing Transactions

Module 5:  Statistics, Probability & Business Analytics

Overview of Statics

  • Data types and their measures
  • Arithmetic Mean, Harmonic Mean, Geometric Mean
  • Meadian, Mode, Variance, Standard Deviation
  • Quartile: First quartile, Second quartile, Third quartile, IQR

Probability Distribution

  • Introduction of probability, Conditional probability
  • Normal distribution, Uniform distribution , Frequency distribution, Central limit theorem

Module 6: Power Bi

  •  Introduction to Power BI, Uses Of Power Bi, The Flow Of Work In Power Bi,
  •  Working With Power Bi, Basic Components Of Power Bi
  •  Comparison Of Power Bi Version, Data Model And Importance Of Data Modeling
  •  Data Sources: How to connect and import data from different sources (Excel etc)

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