Data Analytic From Beginner To Advance

Learn Data Analytics with Excel & Power BI: Data Cleaning, Visualization, Dashboards & Business Insights

What you'll learn

Understand the data analytics lifecycle and apply the problem-solving framework to real-world challenges.

Clean, analyze, and visualize data using Microsoft Excel, including pivot tables and advanced formulas.

Build interactive dashboards in Power BI to communicate insights and track KPIs.

Apply statistical techniques like hypothesis testing and correlation to drive data-informed decisions.

Create a personal portfolio website to showcase your analytics projects and skills to potential employers.

Complete real-world projects and case studies from start to finish, simulating professional data tasks.

Requirements

No prior experience is required—this course is designed for complete beginners!

Willingness to learn and practice

A stable internet connection

A laptop or desktop computer (Windows or Mac)

A Microsoft Excel (guided in the course)

A free Power BI (guided in the course)

Description

Ready to launch your data analytics career using easy-to-learn, in-demand tools? This comprehensive course will take you from beginner to advanced with just Excel and Power BIStart by mastering Microsoft Excel: you’ll learn essential skills like data cleaning, applying formulas, conditional formatting, creating charts, and working with pivot tables. Once you're comfortable with Excel, you'll transition to Power BI, where you'll discover how to import data, establish relationships, apply DAX (Data Analysis Expressions), and create interactive dashboards using visuals and slicers. These skills are essential for analyzing and visualizing data effectively, helping you solve real-world business problems.This course is designed specifically for beginners, non-technical professionals, and anyone looking to switch careers to data analytics. Whether you want to enhance your current skill set or build a new career in data, this course provides hands-on experience and real-world case studies. By the end, you’ll have the confidence to analyze complex data and create stunning reports and dashboards, all while building a portfolio that demonstrates your new skills to potential employers.Tools You’ll Learn:Microsoft Excel: Data cleaning, formulas, charts, pivot tables, conditional formatting, and data visualization.Power BI: DAX, data modeling, relationships, visuals, slicers, and dynamic reports.Projects You’ll Build:Sales Performance AnalysisProject Management AnalysisWho This Course is For:Beginners exploring data analytics careersBusiness professionals working with Excel dataJob seekers looking to build a data portfolioStudents, freelancers, and non-coders

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 What To Expect In This Course

Lecture 3 Free Video

Lecture 4 Free Video

Lecture 5 Free Video

Lecture 6 Free Video

Lecture 7 Free Video

Section 2: Data sources and access

Lecture 8 How to install microsoft excel on windows

Lecture 9 An introduction to spreadsheets

Lecture 10 Important spreadsheet terminology

Lecture 11 Spreadsheet file format

Lecture 12 Spreadsheet text file format

Lecture 13 How to import data into Microsoft excel through Get Data feature.

Section 3: Function you need to know as a data analyst

Lecture 14 10 Basic function in Microsoft Excel

Section 4: Problem solving skills and data analytics process

Lecture 15 Problem Solving

Lecture 16 Data analysis process

Section 5: Data aggregations and descriptie statistics

Lecture 17 Descriptive Statistics

Lecture 18 Pivot Table Overview

Lecture 19 Pivot Table Walkthrough

Section 6: An introduction to data visualisation

Lecture 20 Data Visualization Intoduction

Lecture 21 Data Visualization Walkthrough

Section 7: Samples and distributions

Lecture 22 Sample and sample size

Lecture 23 Hypothesis testing

Lecture 24 Hypothesis testing walkthrough

Section 8: Indentifying patterns

Lecture 25 Line of best fit

Lecture 26 Line of best fit equation

Lecture 27 Line of best fit walkthrough

Section 9: Microsoft Excel Project

Lecture 28 Micorsoft Project Introduction

Lecture 29 Microsoft Excel Project: Data Importation

Lecture 30 Microsoft Excel Project: Data Cleaning

Lecture 31 Microsoft Excel Project: Data Transformation

Lecture 32 Microsoft Excel Project: Exploratory Data Analysis

Lecture 33 Microsoft Excel Project: Data Modeling

Lecture 34 Microsoft Excel Project: KPI

Lecture 35 Microsoft Excel Project: Analysis

Lecture 36 Microsoft Project: Data Visualization

Lecture 37 Microsoft Excel Project: Template

Lecture 38 Microsoft Project: Import KPI to Dashboard

Lecture 39 Microsoft Project: How to design Line Chart

Lecture 40 Microsoft Project: How to design Doughnut Chart

Lecture 41 Microsoft Project: How to design Bar Chart

Lecture 42 Microsoft Project: How to design Column Chart

Lecture 43 Microsoft Project: How to design a Doughnut Chart 2

Lecture 44 Microsoft Project: How to design Slicer

Lecture 45 Microsoft Project: How to design Title

Section 10: Communicating our findings

Lecture 46 Crafting experiences through data stories

Lecture 47 EPIC communication

Section 11: Design for impactful communication

Lecture 48 The four pillars of effective communication design

Lecture 49 Presentation design principles

Section 12: Introduction to dashboard and reporting

Lecture 50 Dashboards and reports

Lecture 51 Power BI as a dashboarding tool

Lecture 52 How to install Power BI into Windows Laptop

Lecture 53 Importing data in Power BI

Section 13: Creating Visuals in Power BI

Lecture 54 Creating a visualization

Lecture 55 Comparisons in Power BI: Line charts

Lecture 56 Comparisons in Power BI: Column charts

Lecture 57 Compositions in Power BI

Lecture 58 Relationships in Power BI: Scatter Charts

Lecture 59 Maps in Power BI

Section 14: Formatting Visuals in Power BI

Lecture 60 Basic formatting of visualisations

Lecture 61 Communicating additional information through visualisations

Lecture 62 Conditional formatting in Power BI

Section 15: Data Model in Power BI

Lecture 63 An introduction to data models in Power BI

Lecture 64 Importance of data model

Section 16: Data Transformations In Power Bi

Lecture 65 Getting started with Power Query Editor

Lecture 66 Data type in power bi

Lecture 67 Spliting and replacing value in power bi

Lecture 68 Analyzing data profile and groupby with power query

Section 17: Calculated Column With Dax

Lecture 69 Concatenating column using dax

Lecture 70 Dax variable

Lecture 71 Using control flow and string functions

Lecture 72 Referencing columns using the RELATED function

Section 18: Dax Aggregation

Lecture 73 Creating a simple year table

Lecture 74 Creating a table of unique values and descriptions

Lecture 75 Creating a simple measure

Lecture 76 Creating a compound measure

Section 19: First Power BI Project

Lecture 77 Dashboard planning

Lecture 78 Creating power BI template with power point

Lecture 79 Project: Dashboard KPI

Lecture 80 Project: Creating a quick measure

Lecture 81 Project: Creating calendar table with dax

Lecture 82 Project: Creating growth rate

Lecture 83 Project: Formating line chart

Lecture 84 Project: Formating doughnut chart

Lecture 85 Project: Formating bar chart and creating conditional column with power query

Lecture 86 Project: Formating slicer

Lecture 87 Project: Creating a greating message

Lecture 88 Project: How to hide some element on your dashboard

Lecture 89 Project: Dynamically add image into dashboard

Lecture 90 Project: Creating a drillthrough in your dashboard

Section 20: Exploratory data analysis in power bi

Lecture 91 EDA Overview

Lecture 92 EDA Key Influncer

Lecture 93 Power BI analyze feature

Lecture 94 Looking for trends and patterns with conditional formating

Section 21: Final Project: Tracking Njiwa’s Water Funds

Lecture 95 Project: Formating column chart

Lecture 96 Final Project: Project Overview

Lecture 97 Final Project: Data Importation

Lecture 98 Final Project: Data Cleaning

Lecture 99 Final Project: Data Modeling

Lecture 100 Final Project: Data Enrichment

Lecture 101 Final Project: Calculate Water Improvement Percenatage

Lecture 102 Final Product: Calculate Cumulative Cost and Budget

Lecture 103 Final Project: Calculating Incompleted Project

Lecture 104 Final Project: Calculating Other Metrics

Lecture 105 Final Project: Importing Template From Power Point Into Power BI Desktop

Lecture 106 Final Project: Formating Card In Power BI Desktop Desktop

Lecture 107 Final Project: Formating Guage Map Power BI Desktop

Lecture 108 Final Project: Formating Bar Chart Power BI Desktop

Lecture 109 Final Project: Formating Pie Chart Power BI Desktop

Lecture 110 Final Project: Formating Shape Map Power BI Desktop

Lecture 111 Final Project: Creating Buton Power BI Desktop

Section 22: Portfolio Website

Lecture 112 Creating A Portfolio Website.

Complete beginners who want to start a career in data analytics,Students and recent graduates looking to build job-ready skills in Excel, SQL, and Power BI,Professionals in non-technical roles who want to make data-driven decisions,Career switchers seeking hands-on experience and a portfolio to break into tech,Freelancers and entrepreneurs who want to analyze their own business data,Anyone interested in learning how to turn raw data into actionable insights and impactful dashboards