Data Analysis Essentials - Prinstine Group Of Companies
Data Analysis Essentials – Prinstine Academy
PA

Prinstine Academy

Data Analysis Essentials

Data work

Data Analysis Essentials Excel • Python • Power BI

Turn numbers into decisions. Learn to clean, analyze, and visualize data—then ship dashboards people actually use.

Enroll Now View Syllabus

Job-Ready Skills

Hands-on with Excel, Python, and Power BI so you can build real dashboards and reports.

Real Project

Ship a capstone using real datasets—perfect for your portfolio or promotion case.

Certificate Included

Earn a Prinstine Academy certificate to show employers you’re ready.

What You’ll Learn

  • Data analysis basics & workflow
  • Excel for cleaning, formulas, PivotTables & dashboards
  • Python (Pandas) for data wrangling & EDA
  • Visuals with Matplotlib & Seaborn
  • Power BI dashboards & storytelling
Team analyzing data

Syllabus

Duration: 12 weeks • Classes: 2–3 per week • Tools: Microsoft Excel, Python (Pandas, Matplotlib, Seaborn), Power BI

Month 1

Excel for Data Analysis

Week 1: Getting Started with Excel

  • What is data analysis and why use Excel?
  • Overview of Excel interface & navigation
  • Understanding data types (numbers, text, dates)
  • Basic data entry & formatting
  • Sorting & filtering data

Week 2: Basic Excel Formulas & Functions

  • SUM, AVERAGE, COUNT
  • IF statements for decision-making
  • Logical functions: AND, OR
  • Text: CONCATENATE, LEFT, RIGHT, MID
  • Dates: TODAY, DATEDIF

Week 3: Cleaning & Validating Data

  • Remove duplicates
  • Data validation (drop-down lists)
  • Conditional formatting
  • Simple cleaning tricks

Week 4: PivotTables & Dashboards

  • What is a PivotTable & when to use it
  • Create PivotTables to summarize
  • Filter & group data in PivotTables
  • PivotCharts & slicers for interactivity
Month 2

Python for Data Analysis

Week 5: Intro to Python & Jupyter

  • Why Python for data analysis?
  • Install Python & open Jupyter Notebook
  • Python basics: variables, data types, lists, dictionaries
  • Read CSVs with Pandas

Week 6: Cleaning Data in Python

  • Missing data (remove or fill)
  • Filter by conditions
  • Sort & select data
  • Create new calculated columns
  • Work with text in Pandas

Week 7: Exploring & Analyzing Data

  • Groupby & aggregates (sum, mean, count)
  • Join/Merge datasets
  • Simple EDA techniques
  • Hands-on with real datasets

Week 8: Visualizing Data with Python

  • Matplotlib basics (line, bar)
  • Seaborn (scatter, hist, heatmap)
  • Titles, labels & colors
  • Create meaningful visuals to tell a story
Month 3

Power BI for Interactive Dashboards

Week 9: Getting Started with Power BI

  • What is Power BI & its role
  • Interface & navigation
  • Connect to Excel/CSV
  • Clean/transform with Power Query

Week 10: Creating Visual Reports

  • Bar, line, pie charts
  • Filters & slicers for interactivity
  • Visual styles & layouts
  • Map & special visuals

Week 11: Advanced Power BI Features

  • Intro to DAX
  • Calculated columns & measures
  • KPIs, drill-through & tooltips
  • Publish & share dashboards

Week 12: Final Project & Presentation

  • Clean, analyze, & visualize a dataset
  • Build a final Power BI dashboard
  • Present findings & receive feedback

Course Outcomes

Confidently clean & analyze data in Excel
Automate handling & visualize with Python
Build professional interactive dashboards with Power BI
Present insights clearly & effectively

Course Details

Duration
12 weeks (2–3 classes/week)
Tools
Excel, Python (Pandas, Matplotlib, Seaborn), Power BI
Format
In-person / Online (Hybrid)
Certificate
Included on completion
Student learning analytics

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