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Data Analytics Using Python Course

DURATION
6 Months

MODE OF TRAINING
Online/Offline

LEVEL
Advanced

Data Analytics Using Python Course Overview

Learn to extract insights from raw data using Python programming. Master data cleaning, preprocessing, and visualization techniques with Pandas, NumPy, and Matplotlib. Explore statistical analysis and predictive modeling to make informed decisions. Work on real-world projects in fields like finance, marketing, and healthcare. Understand the basics of machine learning for data-driven problem-solving. Develop proficiency in presenting data through dashboards and reports. This course is perfect for aspiring data analysts looking to drive business intelligence.

Storytelling Format (Engaging Narrative)

Imagine a retail company facing declining sales. The managers don’t know why customers are leaving or how to improve their offerings. Enter Data Analytics. By analyzing customer purchase patterns, survey feedback, and seasonal trends, the company discovers that most customers prefer online shopping during weekdays. Using predictive analytics, they forecast a potential boost in sales with targeted ads during those times. With this insight, the company adjusts its marketing strategy, personalizes customer experiences, and doubles its revenue within months. This is the power of Data Analytics.

Data Analytics

Introduction to Data Analytics +
  • Overview of Data Analytics and its applications
    Opportunities and Careers paths in Data Analytics
    Roles and responsibilities of a Data Analyst

MS–Excel (Basic to Advance) +
  • Interface
    Row and Columns
    Keyboard shortcuts for easy navigation
    Data Entry(Fill series)
    Find and Select
    Clear Options
    Ctrl+Enter
    Formatting options(Font,Alignment,Clipboard(copy, paste special))
    Fundamentals of Excel
    Logical and Advanced Functions
    Visualization
    Data Summarization and Connecting to Data
    VBA and Macros

Referencing,Arithemetic Functions +
  • Mathematical calculations with Cell referencing(Absolute,Relative,Mixed)
    Functions with Name Range
    Arithmeticfunctions(SUM,SUMIF,SUMIFS,COUNT,COUNTA,COUNTIFS,
    AVERAGE,AVERAGEIFS,MAX,MAXIFS,MIN,MINIFS)

Logical functions +
  • Logical functions:IF,AND,OR,NESTED IFS,NOT,IFERROR
    Usage of Mathematical and Logical functions nested together.

VLookup, Hlookup, Nested VLookup, Index, Match +
  • LOOKUP
    VLOOKUP
    NESTED VLOOKUP
    HLOOKUP
    INDEX
    INDEX WITH MATCH FUNCTION

Advanced functions +
  • Combination of Arithmatic
    Logical
    Lookup functions
    Data Validation(with Dependent drop down)

Date and Text Functions +
  • Date Functions:DATE,DAY,MONTH,YEAR,
    YEARFRAC,DATEDIFF,EOMONTH Text
    Functions:TEXT,UPPER,LOWER,PROPER,LEFT,
    RIGHT,SEARCH,FIND,MID,TTC, Flash Fill

Data cleaning, Data type identification +
  • Number Formatting(with shortcuts)
    CTRL+T(Converting into an Excel Table)
    Formatting Table
    Remove Duplicate
    SORT
    Advanced Sort
    FILTER
    Advanced Filter

Data Visualization: Conditional Formatting, Charts +
  • Conditional formatting(icon sets/Highlighted colour sets/Data bars/custom formatting)
    Charts:Bar,Column,Lines,Scatter,Combo,Gantt,Waterfall,pie
    Fundamentals of Data Visualization
    Introduction to Power BI
    Data Visualization using Power BI
    Power BI basics
    DAX
    Data Visualization with Analytics
    Dashboard

Data Summarization: Pivot Report and Charts +
  • Pivot Reports:Insert,Interface,Crosstable Reports;Filter,Pivot Charts,
    Slicers:Add,Connect to multiple reports and charts Calculated field, Calculated item

Data Summarization: Dashboard Creation +
  • Dashboard:Types,Getting reports and charts together, Use of Slicers.
    Design and placement: Formatting of Tables,Charts,Sheets,Proper use of Colours and Shapes

Connecting to Data: Power Query, Pivot +
  • Power Query: Interface, Tabs
    Connecting to data from other excel files, text files, other sources
    Data Cleaning
    Transforming
    Loading Data into Excel Query

Power BI +
  • Power BI Introduction and Installation
    Understanding Power BI Background
    Installation of Power BI and check list for installation
    Data Type and Load
    Loading data from multiple sources
    Data type and the type of default chart on drag drop.
    Power BI Visualization
    Understanding Column Chart
    Understanding Line Chart
    Conditional formating
    Power Query Editor
    Loading data from folder
    Understanding Power Query in detail
    Promote header, Split to limiter, Add columns, append, merge queries etc
    Modelling with Power BI
    Loading multiple data from different format
    Understanding modelling (How to create relationship)
    Connection type, Data cardinality, Filter direction
    Making dashboard using new loaded data
    Power Query Editor Filter Data
    Power Query Custom Column & Conditional Column
    Manage Parameter
    Introduction to Filter and types of filter
    Trend analysis, Future forecast
    Customize the data in Power BI
    Understanding Tool tip with information
    Use and understanding of Drill Down
    Visual interaction and customisation of visual interaction
    Drill through function and usage
    Button triggers
    Bookmark and different use and implementation
    Navigation buttons
    Dax Expressions
    Introduction to DAX
    Table Dax, Calculated column, DAX measure and difference
    Calculated Column
    Related, Lookup value, switch, Datedif,Rankx,Date functions
    Dax Measure and Quick Measure

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