Business Intelligence is the process of converting raw data into usable insights. The module of "Introduction to Business Intelligence" will help you to understand how BI works, how to create a strategy, and various BI platforms.

A tableau is a powerful tool used for data analysis and visualization; using it, you will be able to create an amazing and interactive visualization, and that too without coding. This module of "Introduction to Tableau" will help you with the installation of Tableau, its user interface, different usage of Tableau in industry, several real-time use cases from various Business Domains, and the main differences between the Tableau Desktop and Tableau Public.

This lesson will help you learn to connect various data sources from different locations. Also, you will learn about different types of connections and how to connect those connections into a text file, excel file, and databases.

Tableau is the software that allows the user to represent the data in a visual format. To utilize Tableau, this module will cover the installation of Tableau and other basic features for the same.

The Tableau software provides the user with an amazing metadata system that is known as DataSource. The module will cover learnings that are introduction and working of metadata, understanding fields, values, etc.

In this session, you will learn about how to create a join and then how you can combine those joins by using different types of joins such as Inner Join, Right Join, Left Join, etc. This module will also cover the differences between relationships and joins.

Data Blending is a method for combining data from different sources as it brings additional information from a secondary data source; you will also understand about primary and secondary data sources, blend relationships for blending, how to establish a link, multiple links, and major differences between joins, relationships and blending, with knowledge about some limitations of blending.

Visual representation in chart and graph form helps to get detailed information on the data. To understand data in easy form, this module will cover creating charts in Tableau with all the basic and advanced charts.

When you're finished with this lesson, you'll have the skills and knowledge to apply analytics to a worksheet needed to communicate insights effectively to your users. Here you will learn marks card, highlighting, sorting, grouping, constant sets, bins, hierarchies, and much more.

This Data Science with BI course will establish your mastery of filters in Tableau. You'll learn the essential concepts of Filters and gain in-depth knowledge of dimension filters, date filters, visual filters, context filters, and more. Filters is a required skill for many Data Science positions, so jump-start your career with this interactive, hands-on course.

Tableau offers a variety of data analysis tools to easily explore the data and produce effective visualizations converting simple figures into advanced charts. In this lesson, you'll learn how to use Box and whisker's plot, and different types of charts like Bullet, Bar In Bar, Gantt, Waterfall, Funnel, etc. Also, there will be a brief understanding of Step and Jump Lines, World Cloud, and Donut chart.

Start with some basic calculations, different types of calculations, and some Built-In functions. Also learn, Level of detail (Lod), Nested Lod expression with aggregation and replication, KPI table, table calculations, and helper functions.

This lesson will help you with creating parameters, charts, and column selection parameters, dashboard formatting, tooltips visualization, and layout to create interactive and actionable dashboards for mobile, also creating and updating story points.

In this lesson, you will briefly learn about sharing options in Tableau and the best ways to represent export and print your reports easily.

This module helps you understand how to use dashboards in Tableau to empower more meaningful business decisions. You'll be exposed to the concepts of building interactive dashboards with actions, designing dashboards for devices, and story points.

This module will help you understand what Power BI is and understands its features and phases. Here you will know the components, architecture, and building blocks of Power BI.

This module gives you the information you need to start working with the Power BI desktop successfully. From Learning the concepts of Overview of Power BI Desktop, Connecting to a Data Sources, Query Editor, Ribbon to Report, data, and model, this module covers all.

Data transformation is converting the data from one format to another, and the process is part of data management tasks. You'll learn to clean, transform, and manage the data in the module.

Data modeling is the process of creating a simplified diagram of a software system. In this module; you will learn various data modeling concepts from the fundamentals to managing data relationships, cross-filter direction, and many-to-many.

Data Analysis Expressions (DAX) is a programming language used throughout Microsoft Power BI to create calculated columns, measures, and custom tables. Hence, it is one of the most essential modules wherein you will learn the importance of DAX, DAX syntax, Data types, operators, DAX functions, queries, tables, and filtering.

The lesson will cover data visualization with Power BI. Concepts like bookmarks, And selection pane, KPI visuals, Z-Order, and much more are covered in the session.

This lesson will begin with the introduction of the Power BI dashboard. Then it'll design the dashboard and make it interactive for the end-users.

Power BI Report Server is an on-premises report server with a web portal in which you display and manage reports and KPIs. Here you will learn report server basics, web portal, paginated reports, data gateways, and the concept of a scheduled refresh.

During this lesson, you will get in-depth insights into what dashboard is, hands-on training on building a dashboard, layouts, and formatting, interactive dashboards with actions, and designing dashboards for devices along with story points.

Direct connectivity with Power BI helps in importing data and working on large datasets. The lesson will help you to learn live connections To Different Data Sources, Connection To SQL Azure, and much more.

R and Python are both programming languages that can be used in Power BI. This lesson covers Python and R integration with Power BI and using its features in Power BI.

Excel helps you perform complex calculations, data analysis, and much more. In this module, you will know the application of excel and the different industry requirements of Excel.

In this lesson, you will learn how Excel Custom Number Format works, why it is important, and how to apply font, alignment, and number formatting.

The advanced sorting function is used to apply sorts on multiple columns in a report. You will learn how to sort by numbers, text, cell color, font color, cell icon, and custom list at this stage.

Excel can store, maintain, and analyze data into useful information. And this is possible due to Excel's exceptional collection of advanced excel formulas and functions. In this lesson, you will master all of them, including math functions, text functions, conditional logical functions, and more.

This module aims at making you learn the advanced data validation techniques that can help you when you are modeling a complex worksheet. You will learn number, date, and time validation, formula-based validation, error message, circle invalid data, and more.

Learn all about Excel's lookup & reference functions, such as VLOOKUP, HLOOKUP, VLOOKUP & HLOOKUP with exact match and approx match.

INDEX and MATCH is the most popular tool in Excel for performing more advanced lookups. Our experts will teach you Index functions, match functions, index with match, and how index match is different from Vlookup.

Pivot tables enable data analysts to summarize large datasets into a concise and meaningful table. You will learn why Pivot Tables for Data Analysis, how to create, and navigate field lists, explore design options, and update them.

Sorting, filtering, and grouping are important functions in Ms. Excel. Get Hands-On experience by learning the working of these elements with pivot tables in Excel.

The lesson will start with the introduction of various charts in Excel and will proceed with different types of charts. Charts like Line charts, Pie & Donut Charts, Clustered Bar charts, and much more will be covered.

After going through the concepts of data analysis, learners will come across the case study of data analysis to understand the concept more clearly.

Get hands-on training on how to create and use Macros, record them, run a macro with a button, edit Macro and learn practical uses of Excel Macro.

This module explains databases, their uses, components, and examples of databases. You will also study database management systems and their history. Finally, you will see types of Databases.

This session will begin with a basic understanding of SQL, followed by RDMS, and Database and table. Finally, you'll also learn about different data types and functions also you'll be able to design your Database and implement data modeling and Queries.

SQL operators have various types. This module teaches about the different types of operators like arithmetic, comparison, logic, etc.

Explore what joins and clauses are, and their types, tables, using joins in tables, work with the variables and queries, Entities and Relationships, DDL & DML Statement, and Functions. Learn theoretically and gain practical exposure too in the module.

A query that is present inside a statement is a subquery. In the module, you'll learn how to write, create, view, insert, delete or update the subquery in SQL.

The module will teach you about views, managing and working with views, some user-defined functions, and finally, what stored procedures are with their working and benefits. Also, you will gain some practical exposure.

Learn why Python is important and which industries work with Python. Get to know the application of Python in different industries and components of Python

Python is a high-level programming language that is used by highly professional as well as beginner learners. In the module, learn to install and set up the programming language, learn about commands,

Learn how to convert raw data into usable format via data wrangling. Get thorough knowledge of exploratory data analysis, model development, model evaluation, etc.

To understand all the concepts of Python clearly, it is important to learn about the fundamental of statistics. Understand the concept of descriptive statistics, inferential statistics, application of statistics, etc.

Numpy is one of the libraries of Python that is used to work with arrays. Learn basic NumPy operators, arithmetic functions, etc.

Panda is a combination of two different libraries that is Matplotlib and NumPy. Learn various concepts in this module, such as DataFrame in Pandas, Series object in pandas, Loading and handling data with Pandas, and much more.

Machine learning is a subset of AI used to make machines much more intelligent and make human work easier. The module begins with an introduction to the concept and other basics of ML.

After learning the basics of ML, learners will start with types of machine learning. All the types are supervised, unsupervised, semi-supervised, and reinforcement machine learning will be covered in the module.

Feature selection is selecting necessary and useful data for the machine learning model. The module will cover topics like how to select the feature selection model, working with feature selection in Python, and much more.

Feature scaling is the process that is performed at the time of data processing that helps in normalizing all the individual values of the data. The module will cover different types of feature scaling and how this is helpful.

PCA is the process that reduces the dimensionality of data and makes it easy to plot it. The module covers how to apply the concept and what its uses are

Discriminant functions are used to classify unknown data in a certain group. The module covers theoretical as well as practical topics of the concepts.

The first lesson in the module includes a basic understanding of concepts, types of supervised learning, real-life applications, and the flow of supervised learning algorithms.

Regression is the process used to identify the relation between dependent and independent variables. Here in this lesson, you will learn what logistic and linear regression is.

As the name suggests, a decision tree is a tree like a flow chart where each brand depicts components like risks, cost, probability, etc. Learn decision tree formation and overfitting in the lesson.

The two most common machine learning algorithms are KNN and SVM. Both algorithms help in the classification of images. The lesson will cover all the related concepts, including the math behind both concepts.

Naive Bayes is a machine learning algorithm that is mainly used in the text classification process. Learners will learn accuracy metrics, confusion matrix, and cost matrix in the lesson.

Start your learning with the basic understanding of unsupervised learning. Learn unsupervised learning real-life applications, unsupervised learning flow, and types of unsupervised algorithms.

Clusters help in grouping similar data by finding the similarity in the patterns. The lesson includes a deep understanding of clusters and an introduction to hierarchical clustering with the help of examples.

PCA stands for principle component analysis that reduces the dimensionality of the data. The module will include the components, steps, and techniques of PCA in detail.