Faculty of Data Science

This module will empower our learners with Microsoft Excel and Power BI basic to advanced skills to work with data for your graphs, data organization and programming. The following topics are covered:

Excel for Data Analytics and Visualization

1. Getting started with Excel
2. Working with data and Excel tables
3. Performing calculations on data
4. Changing workbook appearance
5. Focusing on specific data by using filters
6. Reordering and summarizing data
7. Combining data from multiple sources
8. Analyzing data and alternative data sets
9. Creating charts and graphics
10. Using PivotTables and PivotCharts
11. Using DAX in the Power Pivot Window
12. Printing worksheets and charts
13. Working with macros and forms
14. Working with other Office programs
15. Collaborating with colleagues
16. Manage and share workbooks
17. Apply custom formats and layouts
18. Create advanced formulas
19. Create advanced charts and formulas
20. Using the Analysis Toolpak (Data Analysis)
21. Using the Excel Solver

Power BI for Data Visualization

1. Introduction into Data Visualization Concepts
2. Understanding the basic concept of data visualizations – Understanding Datasets, Data Visualization, Visualization Interpretation
3. Importing Datasets into Power BI
4. Navigating Power BI
5. Understanding the basis of Hierarchy Formation – Drilling Up, Drilling Down
6. Advanced Drilling Options
7. Colours for Enhanced Visualizations
8. Time Series, Aggregation, Granularity and Filters
9. Maps, Scatter Plots and Interactive
10. Custom Visualization Installation
11. Data / Business Forecast with Power BI
12. Creating Relationship among Tables
13. DAX – Data Analysis Expression with Power BI
14. Publishing Report on powerbi.com

CERTIFICATION

While we give you our Certification of Training, we also encourage you to attempt the following global certifications:

• Microsoft Certified: Power BI Data Analyst Associate
• Microsoft Office Specialist: Excel Associate (Office 2019)

In addition, if you are looking at enrolling for an undergraduate or post graduate degree in related course in any institution overseas, this training prepares you ahead for first class degree.

DURATION:

45 Hours

COST:

From ₦100,000 if taken as a stand alone course.

To speak with someone, call +234 (0) 702 630 7268 or +234 (0) 810 402 2323

Beginner Level:

1. Introduction to Data Visualization and Tableau:

   • Overview of data visualization concepts.
   • Introduction to Tableau and its significance.

2. Tableau Interface and Basics:

   • Understanding the Tableau workspace.
   • Connecting to data sources.
   • Data source concepts (Extracts vs. Live Connections).
   • Creating basic visualizations.

3. Data Types and Dimensions:

   • Understanding data types (Continuous vs. Discrete).
   • Working with dimensions and measures.
   • Introduction to the Marks card.

4. Basic Chart Types:

   • Creating bar charts, line charts, and scatter plots.
   • Formatting options for basic visualizations.

5. Filters and Sorting:

   • Implementing filters on visualizations.
   • Sorting data in Tableau.

6. Grouping and Hierarchies:

   • Creating groups and hierarchies for better analysis.
   • Understanding the role of dimensions in hierarchies.

7. Maps in Tableau:

   • Introduction to geographical visualizations.
   • Creating maps and customizing map layers.

Intermediate Level:

8. Advanced Chart Types:

   • Creating advanced visualizations like treemaps, heatmaps, and bubble charts.
   • Dual-axis charts and combo charts.

9. Dashboard Design:

   • Building interactive dashboards.
   • Using actions and filters in dashboards.
   • Best practices for dashboard design.

10. Advanced Calculations:

    • Understanding calculated fields and table calculations.
    • Applying statistical functions in Tableau.

11. Parameters:

    • Creating and using parameters in Tableau.
    • Dynamic control of calculations and filters using parameters.

12. Advanced Mapping:

    • Customizing maps further with background images and spatial files.
    • Implementing map layers and annotations.

Advanced Level:

13. Tableau Server and Online:

    • Introduction to Tableau Server and Tableau Online.
    • Publishing and sharing dashboards.

14. Tableau Integration:

    • Integrating Tableau with other tools (Excel, R, Python).
    • Web Data Connectors (WDC).

15. Advanced Dashboard Actions:

    • Implementing advanced interactivity using dashboard actions.
    • Drill-down and parameter actions.

16. Tableau Prep:

    • Introduction to Tableau Prep.
    • Data cleaning, shaping, and combining data sources.

17. Performance Optimization:

    • Optimizing workbook performance.
    • Extracts vs. Live Connections for better performance.

18. Best Practices and Tips:

    • Best practices for Tableau development.
    • Tips for efficient data visualization.

Capstone Project:

• A hands-on project that requires the application of all the skills learned throughout the training.

CERTIFICATION

While we give you our Certification of Training, we also encourage you to attempt the following global certifications:

• Tableau Certification – https://www.tableau.com/learn/certification

In addition, if you are looking at enrolling for an undergraduate or post graduate degree in related course in any institution overseas, this training prepares you ahead for first class degree.

DURATION:

 30 Hours

COST:

From ₦100,000 if taken as a stand alone course.

To speak with someone, call +234 (0) 702 630 7268.

Learning to work with SQL, this module empowers you to be able to do the following:

• Use SQL for data mining, data analysis, data science, and data visualization
• Transition from the Very Basics to a Point Where You can Effortlessly Work with Large SQL Queries
• Become a Master SQL Developer
• Build awesome dashboards with Google Data Studio and Google Big Query as the backend
• Be confident in using the Google Big Query Tool and Ecosystem
• Practice Every Step of the Way by Working through myriads of practice files.

Modules

• Explaining the theoretical and physical aspects of a relational database
• Relating clauses in SQL Select Statement to Components of an ERD
• Explaining the relationship between a database and SQL

Retrieving Data using the SQL SELECT Statement

• Using Column aliases
• Using The SQL SELECT statement
• Using concatenation operator, literal character strings, alternative quote operator, and the DISTINCT keyword
• Using Arithmetic expressions and NULL values in the SELECT statement

Restricting and Sorting Data

• Applying Rules of precedence for operators in an expression
• Limiting Rows Returned in a SQL Statement
• Using Substitution Variables
• Using the DEFINE and VERIFY commands
• Sorting Data

Using Single-Row Functions to Customize Output

• Manipulating strings with character functions in SQL SELECT and WHERE clauses
• Performing arithmetic with date data
• Manipulating numbers with the ROUND, TRUNC and MOD functions
• Manipulating dates with the date function

Using Conversion Functions and Conditional Expressions

• Applying the NVL, NULLIF, and COALESCE functions to data
• Understanding implicit and explicit data type conversion
• Using the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions
• Nesting multiple functions

Reporting Aggregated Data Using Group Functions

• Restricting Group Results
• Creating Groups of Data
• Using Group Functions

Displaying Data from Multiple Tables

• Using Self-joins
• Using Various Types of Joins
• Using Non equijoins
• Using OUTER joins
• Understanding and Using Cartesian Products

Using Subqueries to Solve Queries

• Using Single Row Subqueries
• Using Multiple Row Subqueries
• Update and delete rows using correlated subqueries

Using SET Operators

• Matching the SELECT statements
• Using the ORDER BY clause in set operations
• Using The INTERSECT operator
• Using The MINUS operator
• Using The UNION and UNION ALL operators

Managing Tables using DML statements

• Managing Database Transactions
• Controlling transactions
• Perform Insert, Update and Delete operations
• Performing multi table Inserts
• Performing Merge statements

Managing Indexes Synonyms and Sequences

• Managing Indexes
• Managing Synonyms
• Managing Sequences

Use DDL to manage tables and their relationships

• Describing and Working with Tables
• Describing and Working with Columns and Data Types
• Creating tables
• Dropping columns and setting column UNUSED
• Truncating tables
• Creating and using Temporary Tables
• Creating and using external tables
• Managing Constraints

Managing Views

• Managing Views

Controlling User Access

• Differentiating system privileges from object privileges
• Granting privileges on tables
• Distinguishing between granting privileges and roles

Managing Objects with Data Dictionary Views

• Using data dictionary views

Managing Data in Different Time Zones

• Working with CURRENT_DATE, CURRENT_TIMESTAMP,and LOCALTIMESTAMP
• Working with INTERVAL data types

CERTIFICATION

While we give you our Certification of Training, we also encourage you to attempt the following global certifications in Database Management

• Oracle Database SQL Certified Associate Certification

In addition, if you are looking at enrolling for an undergraduate or post graduate degree in related course in any institution overseas, this training prepares you ahead for first class degree.

DURATION:

45 Hours

COST:

From ₦100,000 if taken as a stand alone course.

To speak with someone, call +234 (0) 702 630 7268 or +234 (0) 810 402 2323

Python is one of the best languages used by data scientist and machine learning engineers for various projects / application. This module will take learners through our

1. Python Foundation Course where you will learn Python Programming fundamentals.
2. Data Science and Data Wrangling Course where you will learn about data cleaning, data analysis, data engineering, data preprocessing and more
3. Machine Learning Course where you will be taught Machine learning in-depth.

Before the end of this data science and machine learning training experience, learners will work on the following projects:

1. Earthquake prediction
2. Restaurant Recommendation system
3. Cryptocurrency Price Prediction for the next 30days
4. Health Insurance Premium Prediction
5. Financial Budget Analysis
6. Ted-Talks Recommendation System
7. Next word Prediction
8. Movie Recommendation System
9. Image Recognition with Machine Learning
10. Fake News Detection
11. Uber Data Analysis
12. Handwritten Character Recognition
13. Credit Card Fraud Detection
14. Customer Segmentation Using Machine Learning
15. Face Land Marks Detection
16. Car Prices Prediction
17. Python GUI For Data Entry
18. Generate Interactive Map
19. Translate Using Python
20. Exploratory Data Analysis on Global Terrorism
21. Send Custom Email with Python
22. Quiz Game with Python
23. Calculator GUI with Python

Modules:

The Training is organized into the following modules:

PYTHON FOUNDATION

Python programming language is a popular and highly demanded skill. This training will help prepare learners to master Python programming language well enough to break into the world of AI/Machine Learning, Data Science, Data Analytics, Software Engineering and many more.

MODULE 1: Onboarding and Course Introduction

Understanding the difference between Data Analytics, Data Science, Machine Learning, Deep Learning, and Artificial Intelligence. System specification, Jupyter Notebook and GoogleColab Explained, Program Structure and answering all necessary questions to fix learners properly on their career track.

• Python Basics, Data Types, Containers, Operators
• If, else, elif, nested if statement, Loops and functions
• Advance Python

Learners will be given minimum of 5 Projects to work on within the period of 2 weeks and they are advised to submit before the deadline. These projects are applications of what they learnt in module 1 and 2.

DATA WRANGLING

This section of the training will introduce the student into the world of Data Collection, Exploratory Data Analysis, Data Cleaning, Feature Engineering, Data Preprocessing and more. After this academy, Students will be able to perfectly clean data, answer all Data Related Questions and derive insights for any company, organization and individuals that need their services.

Data Visualization is a method that uses static and interactive visuals to help people understand the details embedded in the data being collected. This Program will build student with necessary skills to choose the best chart to visualize data for best decision making.

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