Syllabus

Learning Outline

  • 1

    Welcome to Utiva!

    • Let's get you started

    • SQL Installation Kit

    • Power BI Installation Kit

    • Python Installation Kit

  • 2

    Introduction to Spreadsheet

    • Learning Outcomes

    • Learning Slides : Excel

    • Introduction

    • Introduction to Spreadsheets

    • Save Workbooks, Access recent workbooks _ Pin workbooks

    • Excel Templates

    • Tabs, Ribbons _ Groups

    • Cells, Rows, Columns _ Ranges

    • Inputting _ Formatting Data

    • Creating Basic Excel Formulas

    • Relative _ Absolute Cell References

  • 3

    Structure of an Excel Function

    • Learning Outcomes

    • Structure of an Excel Function

    • SUM() Function

    • MIN() _ MAX() Functions

    • AVERAGE() Function

    • COUNT() Function

    • Adjacent Cell Errors

    • Autosum

  • 4

    Apply simple Formats

    • Learning Outcomes

    • Applying Simple Formats

    • Conditional Formatting

    • Named Ranges and Tables

  • 5

    The IF Command

    • Learning Outcomes

    • Datasets

    • The IF() Function

    • Nested-IF()

    • IFS() Function

    • COUNTIF() Function

    • SUMIF() Function

    • IF ERROR() Function

  • 6

    LookUp, Index and Match

    • Learning Outcomes

    • Datasets

    • VLOOKUP() Function

    • HLOOKUP() Function

    • Submit your Assignment

    • INDEX() Function

    • MATCH() Function

    • INDEX() _ MATCH() Functions

  • 7

    Basic Excel Charts A

    • Learning Outcomes

    • Datasets

    • Basic Excel Charts

    • Pivot Tables

    • Grouping Pivot Tables

    • Calculated Fields in Pivot Tables

    • Filtering Pivot Table Data

    • PivotCharts

    • Filtering with Slicers

  • 8

    Basic Excel Charts (B)

    • Learning Outcomes

    • Datasets

    • Dashboard - 1

    • Dashboards - 2

    • PowerPivot

    • Activating the PowerPivot Add-in

    • Data Models with PowerPivot

    • Creating PivotTables from Data Models

  • 9

    What - IF Analysis

    • Learning Outcomes

    • Datasets

    • What If Analysis - Goal Seek Tool

    • What If Analysis - Solver Tool

    • What If Analysis - Data Tools

    • What If Analysis - Scenario Manager

  • 10

    Data Cleaning

    • Learning Outcomes

    • Datasets

    • Data Cleaning in Excel

    • Importing Data from External Sources - Web Example

  • 11

    Excel Capstone Project

    • Capstone Project

    • Submit your Project

    • Feedback Survey

  • 12

    Live Coaching Session

    • Reinforce Your Learning

  • 13

    LinkedIn Optimization Session [Mid-Term]

    • LinkedIn Optimisation 1

    • LinkedIn Optimisation 2

    • LinkedIn Optimisation 3

    • LinkedIn Optimisation 4

    • LinkedIn Optimisation 5

    • LinkedIn Optimisation 6

    • LinkedIn Optimisation 7

    • LinkedIn Optimisation 8

    • LinkedIn Optimisation 9

    • LinkedIn Optimisation 10

    • LinkedIn Optimisation 11

    • LinkedIn Optimisation 12

    • LinkedIn Optimisation 13

  • 14

    Introduction to PostgreSQL

    • Introduction to PostgreSQL

  • 15

    Introduction to Databases

    • Learning Outcomes

    • Introduction to databases I

    • Introduction to Databases II

    • Introduction to Databases [Presentation]

    • Learning Outcomes

    • Introduction to databases III

    • Introduction to Databases [Presentation II]

  • 16

    Introduction to SQL

    • Learning Outcomes

    • Datasets

    • PostgreSQL Installation

    • The PostgreSQL GUI I

    • The PostgreSQL GUI II

    • The PostgreSQL GUI III

    • Importing CSV Files to pgAdmin I

    • Importing CSV Files to pgAdmin II

    • Submit your Assignment

  • 17

    Querying, Sorting, Filtering and Grouping Data

    • Learning Outcomes

    • Simple SELECT statements I

    • Simple SELECT statement II

    • Simple SELECT statement III

    • Filtering Query Results with WHERE Clause I

    • Filtering Query Results with WHERE Clause II

    • Filtering Query Results with WHERE Clause III

    • Aggregate Functions

  • 18

    Subqueries

    • Learning Outcomes

    • Subqueries in the SELECT Clause

    • Subqueries in the FROM Clause

    • Subqueries in the WHERE Clause

    • Subqueries ANY _ ALL Operators

    • Submit your Assignment

  • 19

    SQL Joins

    • Learning Outcomes

    • Datasets

    • Basics of Joins

    • Inner Joins

    • Left Joins

    • Right Joins

    • Full Joins

    • Union and Union All

  • 20

    Data Cleaning

    • Learning Outcomes

    • Datasets

    • SQL Data Cleaning (String and CONCAT() Function)

    • REPLACE() Function

    • UPPER() _ LOWER() Functions

    • LENGTH() Function

    • LTRIM(), RTRIM() and BTRIM() Functions

    • SUBSTRING(), LEFT() and RIGHT() Functions

  • 21

    Live Coaching Session

    • Reinforce Your Learning

  • 22

    Date Functions, Views and Case Statement in SQL

    • Learning Outcomes

    • Date Function I

    • Date Function II

    • PostgreSQL Views

    • CASE Statements

  • 23

    Wrap Up

    • Datasets

    • SQL Shell

    • Wrap up _ Capstone Project

    • SQL Feedback Survey

    • Submit your Project

  • 24

    Introduction to Power Bi

    • Learning Slide

    • Introduction to Power BI

    • Datasets

    • Learning Outcome

    • Welcome to PowerBI

    • Introduction to PowerBI

  • 25

    Data Preparation and Transformation

    • Learning Outcomes

    • Learning Slide

    • Data Preparation and Transformation

  • 26

    Live Coaching Session

    • Reinforce Your Learning

  • 27

    Data Model and Dax

    • Learning Outcomes

    • Learning Slides

    • Data Model and Dax

    • Submit your Assignment

  • 28

    Data Visualization

    • Learning Outcomes

    • Learning Slide

    • Data Visualisation [Creating Dashboard]

    • Submit your Assignment

  • 29

    Build Interactive Dashboards for Storytelling

    • Learning Outcomes

    • Learning Slide

    • Creating Interactive Dashboards

    • Submit your Assignment

  • 30

    Live Coaching Session

    • Reinforce Your Learning

  • 31

    Power BI Capstone Project

    • Power BI Capstone Project

    • Submit your Project

    • Feedback Survey

  • 32

    Data Science with Python: Basic Operations

    • Data Science with Python: Data Set

    • 01. Intro

    • 02 - What is Python

    • 03 - Overview of the Jupyter Notebook

    • 04 - Basic operations in Python - Print() Function

    • 05 - Basic operations in Python - Basic Arithmetic Function

    • 06 - Basic operations in Python - Variables

    • 07 - Basic operations in Python - Project 1

    • 08 - Project 1 Solution

  • 33

    Data Science with Python: Basic Data Types

    • 09 - Basic data types - Strings.

    • 10 - Basic data types - Numeric data types.

    • 11 - Data Structures - Lists

    • 12 - Data Structures - Tuples

    • 13 - Data Structures - Dictionaries

    • 14 - Data types and Structures - Project 2

    • 15 - Project 2 Solution

  • 34

    Data Science with Python: Control Flow in Python

    • 16 - Control flow in Python - Overview

    • 17 - Control flow in python - Conditional Statements.

    • 18 - Control Flow in Python - For Loops

    • 19 - Control Flow in Python - While Loops.

    • 20 - Control Flow in Python - Project 3

    • 21 - Project 3 Solution

  • 35

    Data Science with Python: Functions and Modules in Python

    • 22 - Functions and Modules in Python - Functions.

    • 23 - Functions and Modules in Python - Lambda Functions.

    • 24 - Functions and Modules in Python - Modules

    • 25 - Functions and Modules in Python - Project 4

    • 25b - Project 4 Solution.

  • 36

    Data Science with Python: Numpy

    • 26 - Numpy - Introduction to Numpy.

    • 27 - Numpy - Creating Arrays in Numpy.

    • 28 - Numpy - Indexing & Slicing Arrays.

    • 29 - Numpy - Copy & View in Numpy.

    • 30 - Numpy - Shape and reshaping Arrays.

    • 31 - Numpy - Basic Operations in Numpy Arrays.

    • 32 - Numpy - Data Analytics Operations in Numpy

    • 33 - Numpy - Project 5

    • 34 - Numpy - Project 5 Solution.

  • 37

    Data Science with Python: Pandas

    • 35 - Pandas - Introduction to Pandas.

    • 36 - Pandas - Reading in Files in Pandas.

    • 37 - Pandas - Looking at data in our dataframe.

    • 38 - Pandas - Accessing, Filtering and Sorting Data in Pandas.

    • 39 - Pandas - Indexing, loc & iloc in Pandas.

    • 40 - Pandas - Groupby and aggregate functions in Pandas.

    • 41 - Pandas - Merge, Join, and Concatenate in Pandas.

    • 42 - Pandas - Data Cleaning in Pandas 1.

    • 43 - Pandas - Data Cleaning in Pandas 2.

    • 44 - Pandas - Data Visualization in Pandas

    • 45 - Pandas - Project 6

    • 46 - Pandas - Project 6 Solution.

  • 38

    Data Science with Python: Matplotlib

    • 47 - Matplotlib - Introduction to Matplotlib.

    • 48 - Matplotlib - Basic plots in Matplotlib.

    • 49 - Matplotlib - Project 7

    • 50 - Project 7 Solution.

  • 39

    Data Science with Python: ML and Regression

    • 52 - Machine Learning - Introduction to Machine Learning.

    • 53 - Machine Learning - Supervised & Unsupervised Learning.

    • 54 - Machine Learning - Machine Learning Techniques.

    • 55 - Machine Learning - Introduction to Scikit-Learn.

    • 56 - Regression with Scikit-Learn - Introduction to Regression Models

    • 57 - Regression with Scikit-Learn - Building your First Linear Regression 1

    • 58 - Regression with Scikit-Learn - Building your First Linear Regression Model 2.

    • 59 - Regression with Scikit-Learn - Building your First Linear Regression Model 3.

    • 60 - Regression with Scikit-Learn - Building your First Linear Regression Model 4.

    • 61 - Regression with Scikit-Learn - Project 8

    • 62 - Project Solution.mp4

  • 40

    Data Science with Python: Classification

    • 63 - Classification with Scikit-Learn - Introduction to Classification Models.

    • 64 - Classification with Scikit-Learn - Building your First Classification Model 1

    • 65 - Classification with Scikit-Learn - Building your First Classification Model 2

    • 66 - Classification with Scikit-Learn - Building your First Classification Model 3

    • 67 - Classification with Scikit-Learn - Building your First Classification Model 4

    • 68 - Classification with Scikit-Learn - Project 9

    • 69 - Project 9 Solution

  • 41

    Data Science with Python: Clustering

    • 70 - Clustering with Scikit-Learn - Introduction to Clustering Models.

    • 71 - Clustering with Scikit-Learn - Building your first Clustering Model 1

    • 72 - Clustering with Scikit-Learn - Building your first Clustering Model 2

    • 73 - Clustering with Scikit-Learn - Project 10

    • 74 - Project 10 Solution.

    • 75 - Wrap-Up.mp4

  • 42

    Sharpening Your Soft Skills for Jobs

    • Welcome to the Jobberman x Utiva Employability Program

    • Sharpening Your Soft Skills

    • Welcome to the SkilledUp Life UK x Utiva Employability Program

    • Practice what you have learnt so far.

    • Student Feedback

  • 43

    Virtual Projects [Post-Training]

    • Welcome to your Virtual Projects Program!

    • Indicino Capstone Project

    • AGCC Capstone Project