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Data Visualization and Analytics Course Content

Introduction to Python Programming

Lesson 1: Introduction to Python

• What is Python?

• Python history and versions

• Setting up Python environment (IDEs, Jupyter Notebook)

Lesson 2: Python Basics

• Python syntax and structure

• Variables, data types, and type conversion

• Basic input and output (I/O) operations

Lesson 3: Control Flow

• Conditional statements (if, elif, else)

• Loops (for, while)

• Break and continue statements

Lesson 4: Functions

• Defining and calling functions

• Parameters and return values

• Scope and lifetime of variables

Lesson 5: Data Structures

• Lists, tuples, and dictionaries

• Indexing and slicing

• List comprehensions

Advanced Python Topics

Lesson 1: Advanced Data Structures

• Sets and frozensets

• Stacks and queues

• Using collections module (Counter, defaultdict)

Lesson 2: Functional Programming

• Lambda functions

• Map, filter, and reduce

• Decorators and closures

Lesson 3: Database Connectivity

• Connecting to databases (SQLite, MySQL)

• Executing SQL queries

• Database CRUD operations

Lesson 4: Web Scraping with Python

• Introduction to web scraping

• BeautifulSoup and requests library

• Scraping data from websites

Intermediate Python Programmin

Lesson 1: File Handling

• Reading and writing text files

• Working with CSV and JSON files

• Exception handling (try, except, finally)

Lesson 2: Object-Oriented Programming (OOP)

• Classes and objects

• Inheritance and polymorphism

• Encapsulation and abstraction

Lesson 3: Modules and Libraries

• Importing modules and libraries

• Creating and using custom modules

• Exploring Python's standard library

Python

Excel

Introduction to Excel Basics

Lesson 1: Introduction to Excel

• Overview of Excel interface

• Understanding workbooks, worksheets, cells, and columns

Lesson 2: Data Entry and Formatting

• Entering and editing data

• Formatting cells, fonts, borders, and alignment

Lesson 3: Basic Formulas and Functions

• Simple arithmetic operations

• SUM, AVERAGE, MIN, and MAX functions

• Understanding relative and absolute references

Lesson 4: Data Management Techniques

• Sorting and filtering data

• Data validation and drop-down lists

• Conditional formatting

Advanced Excel Proficiency

Lesson 1: Power Query and Power Pivot

• Introduction to Power Query

• Data cleaning and transformation with Power Query

• Building data models with Power Pivot

Lesson 2: Excel Tips, Tricks, and Best Practices

• Keyboard shortcuts and productivity hacks

• Efficient data validation techniques

• Excel add-ins and online resources

Lesson 3: Excel Tips, Tricks, and Best Practices

• Keyboard shortcuts and productivity hacks

• Efficient data validation techniques

• Excel add-ins and online resources

Lesson 4: Real-life Business Applications

• Practical case studies and examples

• Industry-specific applications of Excel

• Participants' project presentations and feedback

Intermediate Excel Skills

Lesson 1: Advanced Formulas

• IF, VLOOKUP, HLOOKUP, INDEX, MATCH functions

• Nested functions and logical operators.

Lesson 2: Data Analysis Tools

• PivotTables and PivotCharts

• Goal Seek and Scenario Manager

• Using data tables for what-if analysis

Lesson 3: Advanced Charting Techniques

• Combo charts and secondary axes

• Sparklines for data visualization

• Dynamic charts with named ranges

Lesson 4: Macros and Automation

• Introduction to Macros

• Recording and running macros

• Macro security and best practices

Excel

Introduction to Excel Basics

Lesson 1: Introduction to Excel

• Overview of Excel interface

• Understanding workbooks, worksheets, cells, and columns

Lesson 2: Data Entry and Formatting

• Entering and editing data

• Formatting cells, fonts, borders, and alignment

Lesson 3: Basic Formulas and Functions

• Simple arithmetic operations

• SUM, AVERAGE, MIN, and MAX functions

• Understanding relative and absolute references

Lesson 4: Data Management Techniques

• Sorting and filtering data

• Data validation and drop-down lists

• Conditional formatting

Advanced Excel Proficiency

Lesson 1: Power Query and Power Pivot

• Introduction to Power Query

• Data cleaning and transformation with Power Query

• Building data models with Power Pivot

Lesson 2: Excel Tips, Tricks, and Best Practices

• Keyboard shortcuts and productivity hacks

• Efficient data validation techniques

• Excel add-ins and online resources

Lesson 3: Excel Tips, Tricks, and Best Practices

• Keyboard shortcuts and productivity hacks

• Efficient data validation techniques

• Excel add-ins and online resources

Lesson 4: Real-life Business Applications

• Practical case studies and examples

• Industry-specific applications of Excel

• Participants' project presentations and feedback

Intermediate Excel Skills

Lesson 1: Advanced Formulas

• IF, VLOOKUP, HLOOKUP, INDEX, MATCH functions

• Nested functions and logical operators.

Lesson 2: Data Analysis Tools

• PivotTables and PivotCharts

• Goal Seek and Scenario Manager

• Using data tables for what-if analysis

Lesson 3: Advanced Charting Techniques

• Combo charts and secondary axes

• Sparklines for data visualization

• Dynamic charts with named ranges

Lesson 4: Macros and Automation

• Introduction to Macros

• Recording and running macros

• Macro security and best practices

Tableau

Introduction to Tableau

Lesson 1: Introduction to Data Visualization

• What is data visualization?

• Importance of data visualization

• Role of Tableau in data visualization

Lesson 2: Tableau Overview

• Tableau products and editions

• Installing Tableau Desktop

• Getting started with Tableau interface

Lesson 3: Data Connections

• Connecting to data sources

• Importing and live connections

• Data source options and best practices

Lesson 4: Data Preparation

• Data source tab and data profiling

• Data cleansing and transformation

• Joining and blending data

Advanced Tableau Techniques

Lesson 1: Calculations and Expressions

• Creating calculated fields

• Date and string functions

• Logical and aggregate functions

Lesson 2: Parameters and Dashboards

• Introduction to parameters

• Creating interactive dashboards

• Actions and filters in dashboards

Lesson 3: Storytelling with Data

• Building compelling data stories

• Story points and layout

• Interactive storytelling techniques

Basic Tableau Skills

Lesson 1: Basic Visualization

• Creating a simple bar chart

• Working with dimensions and measures

• Sorting and filtering data

Lesson 2: Maps and Geographic Visualization

• Creating maps in Tableau

• Geocoding and custom geocoding

• Adding context to maps

Lesson 3: Aggregation and Granularity

• Understanding data granularity

• Aggregating and disaggregating data

• Level of detail (LOD) expressions

R - a powerful programming language

Introduction to R

Lesson 1: What is R?

• Introduction to R and its significance in data analysis.

Lesson 2: Installing R and RStudio

• Setting up your R development environment.

Lesson 3: R Basics

• Understanding R syntax, variables, and basic operations.

Lesson 4: R Data Types

Introduction to data types in R, including vectors, matrices, data frames, and lists.

Data Visualization

Lesson 1: Introduction to ggplot2

• Creating static and dynamic plots using the ggplot2 package.

Lesson 2: Basic Plots

• Creating bar plots, histograms, scatterplots, and line charts.

Lesson 3: Customizing Plots

• Customizing plot aesthetics, labels, and themes.

Lesson 4: Interactive Visualizations

• Introduction to interactive visualization libraries like Shiny.

Data Manipulation

Lesson 1: Data Import and Export

• Importing data from various sources (CSV, Excel, databases) and exporting results.

Lesson 2: Data Cleaning

• Handling missing data, dealing with outliers, and data transformation.

Lesson 3: Data Subsetting

• Selecting and filtering data based on criteria.

Lesson 4: Data Aggregation

• Summarizing and aggregating data using functions like aggregate and dplyr.

Advanced Topics

Lesson 1: Time Series Analysis

• Analyzing time-series data using R.

Lesson 2: Machine Learning with R

• Introduction to machine learning algorithms and libraries (e.g., caret, randomForest).

Lesson 3: Web Scraping with R

• Extracting data from websites using R.

Mastering Microsoft Power BI

Introduction to Power BI

Lesson 1: What is Power BI?

Introduction to Power BI, its features, and benefits.

Lesson 2: Installing and Setting Up Power BI

Downloading and configuring Power BI Desktop and Power BI Service.

Lesson 3: Power BI Interface

Exploring the Power BI Desktop interface, including the Ribbon and Data View.

Lesson 4: Data Sources

Connecting to various data sources (Excel, databases, web, etc.).

Data Transformation and Cleaning

Lesson 1: Data Loading

Importing data into Power BI Desktop.

Lesson 2: Data Transformation

Cleaning and shaping data using the Power Query Editor.

Lesson 3: Combining Data

Merging and appending tables, handling relationships.

Lesson 4: Data Modeling

Creating relationships, hierarchies, and calculated columns.

Advanced Data Modeling

Lesson 1: DAX (Data Analysis Expressions)

Introduction to DAX for creating calculated columns and measures.

Lesson 2: Time Intelligence

Working with date and time functions.

Lesson 3: Advanced DAX Functions

Aggregations, ranking, and statistical functions.

Lesson 4: Power BI Data Insights

Creating calculated tables and using advanced modeling techniques.

Data Visualization

Lesson 1: Building Visualizations

Creating charts (bar, line, pie), tables, and matrices.

Lesson 2: Formatting and Customization

Customizing visuals, themes, and styles.

Lesson 3: Interactivity

Adding slicers, filters, and drill-through functionality.

Lesson 4: Best Practices

Designing effective and accessible reports.

Collaboration

Lesson 1: Publishing to Power BI Service

• Uploading reports and dashboards to Power BI Service.

Lesson 2: Sharing and Collaboration

• Sharing with colleagues, creating content packs.

Lesson 3: Data Refresh and Scheduling

• Configuring data refresh options.

Lesson 4: Power BI Mobile

• Accessing reports on mobile devices.

FAQ's

What is the duration of each course in this training program?

This is a 16-week program, and the duration of each course may vary. Specific course durations can be found by clicking here.

Can I take multiple courses simultaneously, or do I need to complete one before starting another?

To ensure a manageable learning experience, it's important to consider the workload and prerequisites for each course. Based on this, we offer a sequential learning program.

Are there any prerequisites for these courses?

Prerequisites vary by course. Some may require prior knowledge or experience in the subject matter, while others are suitable for beginners. Be sure to review the course descriptions for detailed prerequisites and recommended skill levels.

Is this training program suitable for beginners with no prior experience in these subjects?

Yes, many of the courses are designed to accommodate beginners. Look for courses labeled as "introductory" or "foundations" if you're new to a particular subject.

What format are the courses offered in?

Courses are offered in an online format. Be sure to check the specific course format when registering.

Can I access course materials and resources after completing the training program?

Yes, the learning platform is accessible via the internet, and video content is not available for download. However, you can download files such as video transcripts, assignment templates, readings, etc., for maximum flexibility. You can access program content from a desktop, laptop, tablet, or mobile device. Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded for later viewing.

Are there any assessments offered upon completion of the courses?

We conduct regular assessments, quizzes, or projects to evaluate your understanding of the course material. Check the course details for information on assessments.

What kind of support and assistance will I receive during the training program?

Support may include access to instructors, discussion forums, peer support, and additional learning resources. The level of support can vary, so review the specific course details to understand what's provided.

Is financial assistance or scholarships available for these courses?

We may offer financial assistance or scholarships based on eligibility. Assistance requests can be sent to contact@upathi.com .

How do I enrol in this training program, and what is the registration process?

To enrol in the training program, simply submit this form to get started with the registration process.

What technology or software will I need for these courses?

Depending on the course, you may need access to specific software or tools. The course descriptions should specify any technical requirements, and our trainers will assist in providing the required software during the course.

Are there any group discounts available for organizations or teams looking to enroll in these courses?

We do offer group discounts for organizations or teams. Contact us at contact@upathi.com to inquire about group rates and availability.

Can I receive a refund if I need to cancel my enrolment or if I'm not satisfied with the course?

You may request a full refund within five days of your payment or 10 days after the published start date of the program, whichever comes later. If your enrolment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to contact@upathi.com .

What is the policy on deferrals?

After the published start date of the program, you have until the midpoint of the program to request a deferral to a future cohort of the same program. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrolment and are subject to the availability of other cohorts scheduled at our discretion. This policy will not be applicable for deferrals within the refund period, and the limit of one deferral per enrolment remains. All deferral requests should be sent to contact@upathi.com .