Programs

Data Analysis

Data Analyst Program

DURATION

250 Hours / 6 Months, Part-Time Evening Course 

PROGRAM DESCRIPTION

Data Analysts are in high demand. Studies suggest a huge shortage in Data Analysts and a constant increase in demand.

This program is an entry point to the world of Data Analysis for beginners and career changers with or without a background in programming.

Students would develop knowledge of market-leading technologies, how to process information, data analysis capabilities, and more. The program would establish students’ technical, analytical, and business skills, through hands-on exercises and a final project

PREREQUISITES

Canddidates for the program are required to have basic Microsoft Excel skills.

PROGRAM TOPICS
  • Introduction to Data Analytics
    • General introduction
    • Analyst role and capabilities required
    • KPI
    • Analyst work circle
    • Introduction to relational database
    • Insights that can be derived from the data
  • SQL for Data Analyst
    • Introduction to MSSQL 
    • Introduction to work environment 
    • Basic SQL query 
    • Calculated columns 
    • Basic built in functions 
    • Sorting the results 
    • Grouping and aggregate  
    • Advance filtering 
    • Working with NULL values 
    • Diagram 
    • Join tables
    • Conditional statement 
    • Related and unrelated nested queries 
    • Most common built in functions 
    • Window functions 
    • CTE (Common Table Expression) 
    • DML (Data Manipulation Language) 
    • DDL (Data Definition Language) 
    • Data analysis using analyst work circle 
    • Writing user scalar functions 
    • Stored procedure
  • Advanced Excel Skills
    • Formulas 
    • Basic and advanced filtering data 
    • Sorting data 
    • Common use build-in functions 
    • Connectivity to outer data source 
    • If functions 
    • VLOOKUP
    • Error handling 
    • What is analysis functionality 
    • Conditional formatting 
    • Charts and chart components 
    • Pivot tables 
    • Pivot charts 
    • Slicers 
    • Dashboarding
  • Data Visualization and Data Analysis with Tableau
    • Introduction to tableau  
    • Connect to data 
    • Connections 
    • Dimensions 
    • Measures 
    • Basic chart types 
    • Grouping 
    • Advance chart types 
    • Combo chart 
    • Dual axis
    • Filtering 
    • Sorting 
    • Hierarchy 
    • Total and subtotals 
    • Calculated fields 
    • Custom aggregations 
    • Logic statements 
    • Dashboards 
    • Exporting a dashboard
  • Python
    • Python fundamentals 
    • Numpy basics 
    • Basic operations and use of operators 
    • Documentation – importance and how to document 
    • Variables and basic data types 
    • Python basic build in functions 
    • String slicing 
    • Conditions 
    • Introduction to Pandas package 
    • Import data from CSV  
    • Pandas data structures: DataFrame, Series 
    • Pandas descriptive methods (head (), tail (), info (), describe () etc.)
    • Filter records by conditions  
    • Complex conditions 
    • Regex 
    • Sorting data
    • Retrieving data 
    • Handling NULL values 
    • Update data 
    • Grouping and aggregations 
    • Pivot table 
    • Cross tab 
    • Merging DataFrame methods 
    • Loops: For, While, Loop flow control 
    • Def functions 
    • Local and global variable 
    • Lambda function 
    • Apply method 
    • Connect to MSSQL 
    • Visualization with Matplotlib 
    • Visualization with Seaborn  
    • Adjusting the graph display 
    • Save data and pictures into Excel file 
    • Make your script a running program
  • Introduction to Big Data

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