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Successful Data Analysts have a unique set of skills, and represent important value to organizations eager to make data-powered business decisions, uncover insights, communicate critical findings, and create data-driven solutions.

EXCEL – POWER BI – TABLEAU – Google Data Studio – MySQL – Python – Web Scraping – Exploratory Data analysis using Numpy/Pandas – Data visualization with Plotly/Dash – Data Preprocessing

 

Prerequisites:

  • NONE

 

Training Program Description:

  •  This Training Program aim is to address several competencies, Data awareness, statistical applications in excel and business intelligence and data software.
  • Build expertise in data manipulation, data visualization and Data analysis using Python. With the skills you learn in a program, you can launch or advance a successful data career. Start acquiring valuable skills right away, create a project portfolio to demonstrate your abilities, and get support from mentors, peers, and experts in the field.
  • The demand for Data Analysis professionals is booming, far exceeding the supply of personnel skilled in this field. The industry is clearly embracing data analysis, embedding it within its fabric. The demand for Data analysis skills by employers — and the job salaries of Data analysts– are only bound to increase over time, as Data becomes more pervasive in society. Data Analysis is a future-proof career.
  • Gain real-world data science experience with projects designed by industry experts. Build your portfolio and advance your data Analysis career.
  • Throughout this program you will practice your Data analysis skills through a series of hands-on labs, assignments, and projects inspired by real world problems and data sets from the industry. You will also complete the program by preparing a Data Analysis capstone project that will showcase your applied skills to prospective
  • Data Analysis is the process of modelling and transforming data into useful information, this information helps us to make a clear, uniform, and right decisions
  • By the end of this Training Program, you should feel comfortable Implementing business intelligence solutions to your organization using tools such as Excel, Power BI, Tableau, Google data studio or Python that improve the current reporting system and add greater depth to the information to aid in the business decision making process.

Projects

  • This program is comprised of many career-oriented projects. Each project you build will be an opportunity to demonstrate what you've learned in the lessons. Your completed projects will become part of a career portfolio that will demonstrate to potential employers that you have skills in data analysis.

 

  • One of our main goals at EAII is to help you create a job-ready portfolio of completed projects. Building a project is one of the best ways to test the skills you've acquired and to demonstrate your newfound abilities to future employers or colleagues. Throughout this program, you'll have the opportunity to prove your skills by building the following projects

 

  • Building a project is one of the best ways both to test the skills you’ve acquired and to demonstrate your newfound abilities to future employers. Throughout this program, you’ll have the opportunity to prove your skills by building the following projects:

 

  • Project 1: Create, and Design Table then make conditional format, make custom sort
    and use Data analysis Icon to get Statistics Values using Excel
  • Project 2: Create Sales Report Using Functions using Excel
  • Project 3: Create Sales Report using Excel
  • Project 4: Import Data to power Pivot and Power Query then create Marketing Report using Excel
  • Project 5: Create HR dashboard using Power BI
  • Project 6: Create Sales dashboard using Power BI
  • Project 7: Create marketing dashboard using Power BI
  • Project 8: Create dashboard using google data studio
  • Project 9: Creating dashboard Using Tableau
  • Data Analysis using BI Tools Final Project
  • Project 10:  Rock paper scissors
  • Project 11:  Hung man
  • Project 12:  Thanos
  • Project 13:  Library System using OOP
  • Project 14:  Bank System using OOP
  • Project 15Wuzzuf Jobs data collecting using web services
  • Project 16:  Diwan Books data collecting system
  • Project 17:  Design E-commerce Database.
  • Project 18:  Ecommerce system database analysis
  • Project 19: Lynda Courses database analysis
  • Project 20: Movies dataset from Kaggle
  • Project 21: Shopping cart dataset from Kaggle
  • Project 22: FIFA dataset from Kaggle
  • Project 23: Google Play Store
  • Project 24: Data Analyst Jobs Analysis
  • Project 25: Uber Analysis
  • Project 26: Sales product data Analysis
  • Project 27: Ecommerce System data Analysis
  • Project 28: Netflix data Analysis
  • Capstone Project

 

program outcomes:

  • You will gain an advanced level of awareness on the types of data, the role of a data Analyst
  • You will learn how to use advanced Excel Statistical functions
  • You will learn how to Transform Data into INSIGHT and INTELLIGENCE using powerful methods of analysis, techniques, and tools
  • You will learn how to gather, transform, model, and visualize data with Power BI and Google data studio
  • You will Learn best practices for data analysis and data presentation
  • You will Learn to ask the RIGHT questions of your data using comparison, trend, ranking, variance, and many other technique
  • You will Learn best practices for the design and setup of interactive dashboards
  • You will feel confident in implementing Excel, Power BI, and Google Data studio data solutions to your organizations.
  • You will learn how to Build a dashboard using excel, power bi and google data studio
  • Perform feature engineering
  • demonstrate an understanding of fundamental principles of data analytics systems and technologies.
  • Able to use standard techniques of mathematics, probability, and statistics to address problems typical of a career in data analysis
  • Use statistical software packages such Python to solve data analysis problems.
  • Communicate results effectively to stakeholders.
  • Send and receive requests from deployed machine learning models.
  • Transition from the Very Basics to a Point Where You Can Effortlessly Work with Large SQL Queries
  • Web Scraping using Python, scrape data and store it locally or globally to access the data sets whenever needed.
  • identifying opportunities for data analysis across many functional areas of the business

 

Program Duration: 218 Hrs

Program Language: English / Arabic

Location: EPSILON AI INSTITUTE | Nasr City Branch | Mohandessin Branch

Participants will be granted a completion certificate from Epsilon AI Institute, USA if they attend a minimum of 80 percent of the direct contact hours of the Program and after fulfilling program requirements (passing both the Final Exam and Project to obtain the Certificate)

 

CURRICULUM

Training Program Curriculum

1. Introduction to Data Analysis

    • What is Data analysis?
    • Data analysis Process
    • What skills, knowledge, and way of thinking does a data analyst need?

2. Basic and Advanced Excel Review

    • Excel Basics
    • Tables
    • Statistics with Excel
      • Working with Analysis Toolpak
        • Descriptive Statistics
        • Mean
        • Median
        • Mode
        • Range
        • Minimum
        • Maximum
        • Skewness
        • Standard Deviation
    • Sort & Filter
    • Condition Format
    • Project#1 create, and Design Table then make conditional format, make custom sort
      and use the Data analysis Icon to get Statistics Values
    • Text functions
    • Logical Functions
    • Statistic Functions
      • Sumif
      • Sumifs
      • Countif
      • Countifs
      • Maxif
      • Minif
      • Averageif
      • Count
      • Counta
      • Subtotals
    • Lookup Functions
      • V lookup
      • H lookup
      • Index
      • Match
      • X lookup
      • Project#2 Create Sales Report Using Functions

3. Data Analysis Using Excel

  • Pivot Tables
    • Preparing Data to Create Pivot Tables
    • Create, design, change the layout and Refresh the pivot table
    • Grouping Data (dates, text, and numbers)
    • Calculated Fields and Items
    • Show Value as
    • Auto Generate Multiple Reports
    • GENERATE GET PIVOT DATA
    • Double click, Filter, Sort, and search & sort filed a list
    • Auto-fit Column Width, Show & Hide Labels, and Custom
      Style
    • Pivot Chart, Format charts, Slicer and Timeline
    • Conditional Format in pivot table
    • Paste Link & Distinct count
  • Working with Power Query: Introduction & Interface
    • Extract data from different Sources
      • Excel
      • Text File
      • CSV
      • Access
      • Web
      • From Folder
    • Project#3 Create Sales Report
    • Power Query Editor
      • Home Tab
        • Choice & Remove Columns
        • Keep & Remove Rows
        • Split column & Grouping By
        • Transform (Change type & Replace Value)
        • Merge & Append Queries
        • Sort & Change Data Source
      • Transform Tab
        • Transpose
        • Pivot & Unpivot Columns
        • Fill & Count Rows
        • Detect Data Type
        • Use the First row as the header
        • Convert to list & Move
      • Add Column Tab
        • Custom From Examples
        • Custom Column
        • Index Column
        • Merge Columns & Extract
        • Standard
        • Date
      • View Tab
        • Show & Hide Applied Steps
        • Show & Hide Formula bar
        • Column Quality & Column Profile
    • Introduction to Data Model & relationships
      • Create Models
    • Introduction to Dax
      • Create Measures
      • Create New Columns
      • Create KPIs
    • Project#4 import Data to power Pivot and Power Query then create Marketing Report Data Visualization with Excel

 

3. Data analysis using Power BI.

    • Introduction & Interface
    • Get Data
      • Excel, CSV, Access, SQL Server, Web and Text
    • Working With Charts
      • Optimum use of each chart
      • Format chart
    • Filter Pane
      • Filter on this visual
      • Filter on this page
      • Filter on all pages
    • Working with all Tabs
      • Home Tab
      • Insert Tab
      • Modeling Tab
      • View Tab
      • Format, Data / Drill
      • Grouping Data
      • Conditional Format
      • Hierarchies
      • Bookmarks, Page tooltip, and Drill through
      • Learn how to Create Professional Dashboard
      • Difference between dashboard & Report
      • How to ask Questions as a data analyst?
      • Statistics for data analyst
      • Data Cleaning by Power Query
      • Reshape Complex Data by Power Query
      • Working with many too many relationships and Star schema
      • Project#5 – create an HR dashboard
      • Working with advanced DAX Functions
        • Time Intelligence functions
        • Aggregation Functions
        • Filter Functions
        • Relationships Functions
        • Logical Functions
        • Other useful functions
      • Project#6 – create a Sales dashboard
      • Working with Power BI Service
        • Publish Reports
        • Create & Manage Workspace
      • Create & work with Parameters
      • Quick Review of all Topics
      • Project#7 – create a marketing dashboard
    • Final Project

4. Data Analysis Using Google Data Studio

      • Overview
      • Access Controls
      • Home Page
      • Create Dashboard
      • Project#8 – create a dashboard Using Google Data Studio

 

5. Data analysis using Tableau.

    • Overview
    • Building and Customizing Visualizations
    • Analytics
    • Collect many Reports
    • Project#9 – Creating a dashboard Using Tableau

 

6. Data Analysis using BI Tools CAPSTONE PROJECT

 

7. Intro to AI World

  • Introduction to Data analysis
  • Introduction to AI
  • Introduction to Machine Learning
  • Introduction to Computer Vision
  • Introduction to NLP
  • Introduction to Autonomous
  • Data analysis Process Activities
  • Data Different jobs (Data Engineer – Data Analyst – Data scientist – ML engineer – MLOps Engineer).
  • Roadmap for data analysis

 

8. Python Programming

  • Environment Setup (Anaconda)
  • Virtual Environments Concept
  • Command Line
  • Conda & pip package managers
  • Jupyter Notebook
  • Why python for data science
  • Intro to python
    • Input & Output
    • Variables
    • Data types
      • Numbers & Math
      • Boolean & Comparison & Bitwise and Logic.
      • Strings – Strings Methods.
    • If Conditions
    • For & While Loops
    • Lists
    • Tuples
    • Sets
    • Dictionaries
    • List Comprehensions
    • Dictionary Comprehensions
  • Exceptions
  • File Handling
  • Functions
  • Built-in functions & Operators (zip, enumerate, range, …)
  • Map, Filter, and Reduce
  • Lambda Expressions
  • PROJECT #10 ROCK PAPER SCISSORS
  • PROJECT #11 HANGMAN
  • Modules & Packages
  • Git & GitHub (Version Control)
  • GitKraken
  • PROJECT #12 PY
  • Object-Oriented Programming (OOP)
    • Classes & Objects
    • Data Hiding and Encapsulation
    • Inheritance
    • PROJECT #13 LIBRARY SYSTEM USING OOP
    • PROJECT #14 BANK SYSTEM USING OOP

9. Data Collecting – (Web Scraping & Web Services)

  • Public datasets websites
  • Network Topologies
  • Internet and Web Servers
  • HTTP Request/Response Cycle
  • Web Services & JSON
  • Intro to HTML and CSS – Online Playlist
  • Scrapping Concept
  • Download Files
  • Beautiful Soap Library
  • PROJECT #15 WUZZUF JOBS DATA COLLECTING USING WEB SERVICES
  • PROJECT #16 DIWAN BOOKS DATA COLLECTING SYSTEM

 

10. Databases & MySQL

  • Tables, Columns, and Data types
  • How to design a database.
  • One-To-Many & Many-To-Many Relationships.
  • MySQL Workbench
  • ACTIVITY DESIGN DATABASE STRUCTURES LIKE FACEBOOK, TALABAT, YOUTUBE
  • PROJECT #17 DESIGN AN E-COMMERCE DATABASE
  • SQL
  • CRUD
  • Selecting data
  • Filtering data
  • Ordering data
  • Limiting data
  • Aggregate Functions
  • Joining tables
  • Grouping data
  • Dealing with the date and time of SQL
  • Subqueries
  • Window Functions
  • Inserting new data
  • Updating data
  • Deleting data
  • Python and MySQL
  • PROJECT #18 ECOMMERCE SYSTEM DATABASE ANALYSIS
  • PROJECT #19 LYNDA COURSES DATABASE ANALYSIS

 

11. Exploratory Data Analysis with NumPy & Pandas

  • EDA Process
  • Linear Algebra
    • Vector's operations
    • Matrix operations
    • Victor Norm
  • NumPy
    • Create NumPy Array
    • Indexing
    • Arithmetic and Logic
    • Universal Array Functions
  • Statistics
    • Understanding data
    • Central Tendency
    • Measures of Dispersions
    • Correlation
    • Normal Distributions
    • Standard Normal Distributions
    • Sample Distribution
    • Central Limit Theorem
    • Confidence Interval
    • Statistical Significance
    • Hypothesis Testing
    • A/B Testing
  • Pandas
    • Series
    • Data Frames
    • Data Input & Output
    • Useful Methods
    • Apply function
    • Grouping data and aggregate functions
    • Merging, Joining, and Concatenating
    • Pivoting
  • PROJECT #20 MOVIES DATASET FROM KAGGLE
  • PROJECT #21 SHOPPING CART DATASET FROM KAGGLE
  • PROJECT #22 FIFA DATASET FROM KAGGLE

 

12. Data Visualization with Plotly & Dash

  • Plotly
    • Distribution Plots
    • Categorical Plots
    • Matrix Plots
  • Dash
    • Customize plots (colors, markers, line styles, Limits, Legends, Layouts
    • Text and Annotations
  • PROJECT #20 MOVIES DATASET FROM KAGGLE CONT.
  • PROJECT #21 SHOPPING CART DATASET FROM KAGGLE CONT.
  • PROJECT #22 FIFA DATASET FROM KAGGLE CONT.

 

13. Data Preprocessing

  • Feature Engineering and Extraction
    • Domain knowledge features
    • Date and Time features
    • String operations
    • Web Data
    • Geospatial features
  • Feature Transformations
    • Data Cleaning or Cleansing
    • Work with Duplicated data
    • Detect and Handle Outliers
    • Work with Missing data
    • Work with Categorical data
    • Deal with Imbalanced classes
    • Split data to Train and Test Sets
    • Feature Scaling
    • Data Preprocessing Mind Map
    • PROJECT #23 GOOGLE PLAY STORE
  • PROJECT #24 DATA ANALYST JOBS ANALYSIS
  • PROJECT #25 UBER ANALYSIS
  • PROJECT #26 SALES PRODUCT DATA ANALYSIS
  • PROJECT #27 E-COMMERCE SYSTEM DATA ANALYSIS
  • PROJECT #28 NETFLIX DATA ANALYSIS

14. Data Analysis CAPSTONE PROJECT

 

Download Certified Data Analyst Professional – CDAP 110 Hrs (without Python) Brochure PDF

    Download Certified Python Data Analyst Professional – CPDAP 128 Hrs (Using Python) Brochure PDF

       

      Download Certified Data Analyst Professional – CDAP 218 Hrs  Brochure PDF

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