Data Science

Basic Excel

Module 1: Introduction to Excel

•   Overview of Microsoft Excel as a powerful spreadsheet software used for data organization and analysis.

Module 2: Spreadsheet Essentials

•   Learn basic functions such as entering data, formatting cells, and navigating worksheets for effective data management.

Module 3: Formulas and Functions

•   Understand essential formulas and functions like SUM, AVERAGE, and IF for performing calculations and analysis.

Module 4: Charts and Graphs

•   Explore tools for creating visual representations of data through charts and graphs, enhancing data interpretation and presentation skills.

Adv.Excel

Module 1: Mathematical & Statistical Functions

•   SUM ,MAX ,MIN ,POWER, SQRT

Module 2: Advanced Mathematical Functions

•   SUMIF, SUMIFS, DSUM ,SUMPRODUCT ,LARGE ,SMALL

Module 3: Statistical Functions

•   COUNT, COUNTA,COUNTBLANK ,COUNTIF,COUNTIFS

Module 4: Working with Databases

•   DGET,DMAX,DMIN

Module 5: Text Manipulation Functions

•   PREFIX,SUFFIX , LEN, SUBSTITUTE,REPLACE

Module 6: Attendance Register

•   Using Functions For Attendance Register
•   Application Of Functions In Managing An Attendance Register.

Module 7: Text Functions And & Functions

•   Using Functions UPPER, LOWER, PROPER ,Text Extraction Functions,LEFT,RIGHT,MID,Combining and Concatenating Text, CONCATENATE, Data Transformation.

Module 8: Logical Functions And Salary Sheet with Logics

•   Basic Logical Function
•   Combining Logical Tests
•   IF AND
•   IF OR
•   Nested Logical Functions (1 hour)
•   Nested IF
•   Nested IF AND
•   Nested IF AND IF OR
•   Creating a Salary Sheet with Logics (1 hour)

Module 9: Financial Functions

•   Basic Financial Calculations
•   PMT (Payment function)
•   IPMT (Interest payment function)
•   PPMT (Principal payment function)
•   AMOUNT PAYABLE (Total amount payable)
•   Time Value of Money
•   PV (Present Value)
•   NPER (Number of periods)
•   RATE (Interest rate)

Module 10: Data Validations And Invoice Creations

•   Data Validation with Indirect Functions
•   Exploring data validation with indirect functions for dynamic validations.
•   No Duplicates Allowed
•   Setting up data validation rules to prevent duplicate entries.
•   Logical Functions
•   IS EVEN
•   IS ODD
•   Using logical functions within data validation.
•   Invoice Creation with GST and Data Validation Features
•   Creating an invoice template with data validation features.
•   Incorporating GST calculations and validations into invoices.

Module 11: IS Functions And Error Handling

•   Testing for Blank Cells
•   ISBLANK
•   Identifying and handling blank cells.
•   Error Checking Functions
•   ISERROR
•   ISERR
•   ISNA
•   Understanding and addressing various error types.
•   Testing for Even and Odd Values
•   ISEVEN
•   ISODD
•   Using IS functions to determine even and odd values.
•   Checking for Formulas and Data Types
•   ISFORMULA
•   ISTEXT
•   ISNUMBER
•   ISLOGICAL
•   ISNONTEXT

Module 12: Conditional Formattings And Advanced Formatting

•   Advanced Conditional Formatting with Formulas
•   Using formulas to create custom conditional formatting rules.
•   Brief Overview of Conditional Formattings with Data Validations
•   Highlighting the combination of data validations and conditional formatting for data control.
•   Brief Introduction to Using a Search Box
•   Explaining the concept of a search box in Excel.
•   Demonstrating Implementation of a Search Box in Conditional Formattings
•   Basic Filter Operations (15 minutes)
•   Using standard filters for data manipulation.
•   Advanced Filtering Techniques (20 minutes)
•   Demonstrating advanced filtering methods to analyze data.
•   Combining Filters with Macros (15 minutes)
•   Integrating basic macros with filtering to automate tasks.
•   Advanced Filtering (20 minutes).
•   In-depth coverage of advanced filtering, including criteria and unique scenarios.

Module 13: VLOOKUP

•   VLOOKUP Function.
•   Normal VLOOKUP.
•   VLOOKUP + MATCH Function.
•   VLOOKUP + ROW Function.
•   VLOOKUP + COLUMN Function
•   VLOOKUP with Arrays and Indirect Functions
•   VLOOKUP + ARRAY Function
•   VLOOKUP + INDIRECT Function
•   VLOOKUP + COLUMN Function
•   VLOOKUP with Aggregations and Logical Functions
•   VLOOKUP + Aggregations
•   VLOOKUP + Logical Function
•   VLOOKUP + IF Error Handling

Module 14: HLOOKUP

•   HLOOKUP Function
•   Introduction to HLOOKUP
•   HLOOKUP + Array Function
•   Other Lookup Functions.
•   Lookup Formulas
•   VLOOKUP with TRUE Functions

Module 15: LOOKUP

•   Other Lookup Functions.
•   Lookup Formulas
•   VLOOKUP with TRUE Functions

Module 16: INDEX + MATCH

•   Finding Data in a Table.
•   Using INDEX + MATCH to retrieve specific data from a table.
•   Example 2: Dynamic Data Retrieval
•   Example 2: Demonstrating how INDEX + MATCH can be used to dynamically fetch data based on changing criteria.
•   Example 3: Cross-Reference Data
•   Showing how to cross-reference data from multiple tables using INDEX + MATCH.
•   Example 4: Advanced Lookup Scenarios
•   Addressing more complex lookup scenarios with INDEX + MATCH.

Module 17: Date Functions And Dynamic Calendar

•   Weekday Function
•   Understanding the WEEKDAY function for identifying the day of the week.
•   Date and EOMONTH Functions
•   Using the DATE function for date calculations.
•   Applying the EOMONTH function to find the end of the month.
•   TODAY and NOW Functions
•   Using the TODAY function to display the current date.
•   Utilizing the NOW function to show the current date and time.
•   Dynamic Calendar Preparation
•   Creating a fully dynamic calendar with date functions, including Weekday, Date, EOMONTH, TODAY, and NOW.
•   Applying conditional formatting to highlight specific dates or events.

Module 18: Advanced Pivot Chart & Tables

•   Advanced Pivot Chart & Tables
•   Building Pivot Tables
•   Creating pivot tables from raw data.
•   Organizing and customizing pivot tables.
•   Calculations in Pivot Tables.
•   Adding calculated fields and items in pivot tables.
•   Using functions and formulas for custom calculations..
•   Advanced Pivot Chart Visualization.
•   Creating advanced pivot charts.
•   Customizing chart styles, labels, and colors.
•   Visualizations in Pivot Charts
•   Exploring different visualization options.
•   Applying advanced charting techniques.
•   Generating Reports.
•   Using pivot tables and charts to generate insightful reports.
•   Organizing and formatting reports for effective communication.

Module 19: Excel Tips And Tricks

• •   Keyboard Shortcuts
  •   Essential keyboard shortcuts for efficiency.
  •   Data Entry and Editing Tricks
  •   Time-saving techniques for data entry and editing.
  •   Calculations in Pivot Tables.
  •   Formatting and Styling Tips
  •   Quick formatting and styling tips to make your documents more appealing.
  •   Formula and Function Tricks
  •   Tips for working with formulas and functions effectively.
  •   Data Analysis Hacks
  •   Techniques for better data analysis and visualization.
  •   Customization and Productivity
  •   Customizing Excel settings and boosting your productivity.

Basic Python

Module1 : Introduction to Python

•   Overview of Python
•   Python Interpreter
•   features of python
•   why python
•   Basic Syntax

Module 2: Tokens in python

•   Definition of identifiers in programming languages.
•   Explanation of their role in uniquely identifying variables, functions, and other entities.
•   Explanation of keywords as reserved words with special meanings in a programming language.
•   How indentation is used to define code blocks instead of explicit braces.
•   Discussion on the ASCII and Unicode character encoding.

Module 3: Identifier rules Mode of python Formatted Input /output

•   Discussion on the rules and conventions for naming identifiers.
•   Users interact with Python prompt directly
•   Reads user input from the console.

Module 4: Datatypes

•   Definition and usage of integers.
•   Explanation of floating-point numbers.
•   Definition of strings as sequences of characters.
•   String manipulation, indexing, and slicing.
•   Introduction to boolean values: True and False.
•   Definition of tuples as ordered, immutable sequences.
•   Understanding the concept of unique elements in a set.
•   Set applications in data analysis and processing.

Module 5: Operators

•  Performing addition and subtraction operations on numeric elements in a list.
•  Overview of bitwise operators (&, |, ^, ~, <>) in Python.
•  Overview of how they test for the presence or absence of a value in a sequence.
•  Definition of operator precedence in Python.

Module 6: Conditional Statement

•   Introduction to Conditional Statements
•   Definition of nested if statements in Python.
•   Ternary operator/short hand if else

Module 7: Looping Statements

•   Understanding how the loop's condition is evaluated.
•   Introduction to Range
•   Definition and purpose of the break statement in Python.
•   Understanding the structure and indentation for nesting.

Module 8: Strings

•   Creating a String
•   Extract string element
•   String Property
•   String Methods
•   String practice set question

Module 9: Functions

•   Introduction to Functions
•   User define functions
•   inbuilt functions
•   function definitions
•   function calling
•   Type of functions
•   positional arguments/required arg
•   default arguments
•   keyword arguments
•   arbitrary positional arguments
•   arbitrary keyword arguments
•   Functions as first class value
•   Lamda function
•   Higher order function
•   map
•   filter
•   reduce

Module 10: list

•   Understanding the concept of order in list elements.
•   Understanding List Characteristics

Module 11: Tuple

•   Creating a tuple
•   Accessing elements from tuple
•   Updating tuple
•   Membership
•   Tuple functions
•   Practical related questions

Module 12: Modules

•   Creating a module
•   Importing a module
•   Importing multiple modules
•   Alias/alias while importing multiple modules
•   Importing single or specific element from module
•   Alias while importing single element
•   Importing a module from another directory Dir()

Module 13: packages

•   Package Structure
•   Directory Hierarchy
•   Importing from a Package
•   Using __init__.py
•   Subpackages
•   Hierarchical Structure
•   practice set questions

Module 14: File handling

•   Create a new file
•   Overwrite an existing one for writing
•   Creating, updating, and analyzing log files aids in monitoring system activities

Module 15: Exception handling

•   Understanding the need for handling exceptions in a program
•   Creating custom exceptions to handle specific situations.
•   Handling exceptions in concurrent and asynchronous programming.

Advance Python

Module1 : Introduction to OOP

•   Overview of classes in Python, defining and using classes.
•   Instantiation of classes, understanding object-oriented principles.
•   Defining and accessing attributes, instance and class methods.

Module 2: Constructor And Destructor Inheritance

•   Understanding __init__ and __del__, their importance and usage.
•   Initialize object state and set default values
•   Extending or modifying functionality in derived classes.
•   Understand how constructors work in a single inheritance scenario.

Module 3: Polymorphism

•   Intoduction to Polymorphism
•   Method overloading
•   method overriding

Module 4: Encapsulation and Abstraction

•   Enhances code organization, security, and maintainability by restricting direct access to internal details of a class.
•   Access control modifiers

Module 5: Regular Expressions

•   Understanding the power of regular expressions, basic syntax.
•   Using match to find patterns at the beginning of strings.
•   Understanding the practical differences and use cases.
•   Exploring commonly used patterns and their applications.

Module 6: Common Gateway Interface

•   Introduction to CGI, its role in web applications.
•   Understanding the CGI architecture and its components.
•   Differences, usage, and handling data with GET and POST.
•   Understanding, creating, and managing cookies in CGI.
•   Implementing file uploads in CGI applications.

Module 7: Database

•   Facilitates database operations in Python
•   Allowing the creation, manipulation, and querying of SQLite databases.
•   Establishes and manages the connection to an SQLite database
•   Points to be remember Before connecting to a MySQL database
•   Handling Errors

Module 8: Networking

•   Communication between devices over a network using sockets
•   Facilitating data exchange.

Module 9: Multithreading

•   Benefits of Using Python for Multithreading
•   Thread modules
•   Thread Creation in Python
•   Thread Lifecycle
•   Thread Synchronization
•   Multithreaded Priority Queue

Module 10: GUI Programming

•   Create the GUI application main window.
•   Add one or more of the above-mentioned widgets to the GUI application.
•   Enter the main event loop to take action against each event triggered by the user.
•   Tkinter Widgets
•   Standard Attributes
•   Geometry Management
•   SimpleDialog:askinteger /askfloat /askstring
•   The FileDialog Module
•   ColorChooser
•   ttk module

Module 11: Sending Emails in Python

•   SMTP
•   Smtplib Module
•   Email Message Components:sender/recipient/subject/body
•   Connection to SMTP Server
•   Sending mails

Module 1: Introduction to Databases and SQL

•   Introduction to databases and their importance Overview of relational databases and SQL
•   What is SQL (Structured Query Language)?History and evolution of SQL

Module 2: Basic SQL Queries

•   Retrieving Data with SELECT Statement
•   Syntax of the SELECT statement
•   Retrieving data from a single table

Module 3: Grid Layout Examples

•   Creating responsive layouts with grid classes
•   Understanding grid breakpoints and responsive design

Module 4: Filtering Data with WHERE Clause

•   Filtering rows using WHERE clause
•   Using comparison operators and logical operators

Module 5: Sorting and Filtering Data

•   Sorting Data with ORDER BY Clause
•   Sorting query results using ORDER BY clause.
•   Sorting by single or multiple columns.

Module 6: Filtering Data with DISTINCT and LIMIT

•   Using DISTINCT to remove duplicate rows
•   Limiting the number of rows returned with LIMIT clause

Module 7: Aggregating Data

•   Aggregate Functions: SUM, AVG, COUNT, MIN, MAX
•   Introduction to aggregate functions
•   Calculating total, average, count, minimum, and maximum values

Module 8: Working with Multiple Tables

•   Introduction to Joins
•   Understanding table joins in SQL
•   Types of joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN

Module 9: Subqueries

•   Understanding subqueries and their syntax

Module 10: Set Operations Inserting Data with INSERT Statement

•   UNION, INTERSECT, EXCEPT
•   Inserting new rows into a table using INSERT statement
•   Specifying column names and values in INSERT statement

Module 11: Views, Indexes

•   Creating and Managing Views
•   Creating views to simplify complex queries
•   Managing and modifying views in SQL

Module 12: Implementing Data Integrity with Constraints

•   Defining constraints: NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY
•   Enforcing data integrity rules with constraints

Module 13: Transactions and Concurrency Control

•   Introduction to Transactions
•   Understanding transactions and their properties: ACID Beginning, committing, and rolling back transactions

Module 1: Introduction to Tableau

•   Tableau Course Material
•   Learn Tableau Basic Reports
•   Learn Tableau Charts
•   Learn Tableau Advanced Reports
•   Learn Tableau Calculations & Filters
•   Learn Tableau Dashboards
•   Server

Module1 : Introduction to Power BI

•   Introduction to Power BI and its role in data analysis and visualization.
•   Installation Process
•   A step-by-step guide to installing Power BI.
•   Power BI Interface
•   Introduction to the various tabs in the Power BI interface.
•   Basics of Data Handling
•   Overview of how Power BI handles data, including data import and preparation.
•   Introduction to Visualizations
•   Exploring the visualization options available in Power BI.
•   Data View, Model View, and Power Pivot.
•   Understandingderstanding the different views in Power BI: Data View, Model View, and Power Pivot.

Module 2: Basic Charts and Data Import

•   Data Types and Data Import
•   Introduction to different data types and importing data from Excel and CSV files.
•   Overview of Visuals
•   Explanation of visuals and their role in Power BI.
•   Creating a Column Chart
•   How to create and customize a column chart.
•   Stacked Column Chart
•   Creating and working with stacked column charts.
•   Pie Chart and Donut Chart
•   Creating and configuring pie and donut charts.
•   Funnel Chart
•   Introduction to funnel charts and their use.
•   Ribbon Chart
•   Creating ribbon charts for data representation.
•   Data Transformation
•   Keep Only and Exclude operations to manage data.
•   Data Exploration and Export
•   Viewing data and exporting results for further analysis.

Module 3:Maps in Power BI

•   Overview of maps as a visualization option in Power BI.
•   Map Chart
•   Exploring how to create a basic map chart in Power BI.
•   Filled Map.
•   Understanding and using the filled map chart.
•   Map with Pie Chart
•   Combining map visuals with pie charts for data representation.
•   Formatting in Maps.
•   Pie Chart and Donut Chart
•   Customizing map visuals to enhance data presentation.
•   Background Changes in Maps
•   Modifying map backgrounds for improved visualization.
•   Maps of India
•   Creating and customizing maps specific to India.
•   Maps of Australia
•   Creating and customizing maps specific to Australia.

Module 4:Tables and Matrices in Power BI

•   Creating a Simple Table
•   How to create a basic table in Power BI.
•   Formatting a Table
•   Customizing the appearance and layout of a table.
•   Conditional Formatting in Table
•   Applying conditional formatting to tables for data visualization.
•   Creating a Matrix in Table
•   Constructing matrices within tables for enhanced data representation.
•   Conditional Formatting in Matrix
•   Implementing conditional formatting in matrices for better insights
•   Automatic Hierarchy in Matrix
•   Utilizing automatic hierarchy features within matrices.
•   Subtotal and Grand Total
•   Adding subtotal and grand total features to tables and matrices.
•   Number Formatting in Table and Matrix
•   Applying number formatting to tables and matrices for clarity.

Module 5:Tables and Matrices in Power BI

•   Line Chart
•   Creating and customizing line charts for data representation.
•   Drill Down in Line Chart
•   Implementing drill-down functionality within line charts for deeper insights.
•   Area Chart
•   Using area charts to visualize data trends.
•   Line vs. Column Chart
•   Comparing and contrasting line and column charts for different scenarios.
•   Scatter Plot
•   Creating scatter plots for correlation analysis.
•   Waterfall Chart
•   Creating and formatting waterfall charts for data breakdowns.
•   Tree Map
•   Using tree maps to display hierarchical data..
•   Gauge Chart
•   Building gauge charts for data measurement.

Module 6:Cards and Filters in Power BI

•   Number Card
•   Creating and customizing number cards for numeric data.
•   Text Card
•   Setting up text cards to display textual information.
•   Date Card
•   Creating date cards to showcase date-related data.
•   Multi-Row Card
•   Using multi-row cards for detailed data representation.
•   Filter on Visuals
•   Applying filters to individual visuals in Power BI.
•   Filter on Page
•   Implementing filters that apply to an entire page.
•   Filter on All Pages
•   Creating filters that affect all pages in the report.
•   Drill-Through
•   Setting up drill-through functionality for detailed data exploration.

Module 7:Slicers in Power BI

•   Slicers for Text
•   Creating and using slicers for text data.
•   Formatting Text Slicers
•   Customizing the appearance of text slicers.
•   Slicers for Dates
•   Implementing date slicers for date-based data filtering.
•   Formatting Date Slicers
•   Customizing the appearance and format of date slicers.
•   Slicers for Numbers
•   Using number slicers for numeric data filtering.

Module 8:Advanced Charts in Power BI

•   Animated Bar Chart Race
•   Creating animated bar chart races to visualize data trends over time.
•   Drill-Down Donut Chart
•   Implementing drill-down functionality within donut charts for deeper insights.
•   Word Cloud
•   Generating word clouds to analyze textual data.
•   Sankey Chart
•   Using Sankey charts to represent flow and relationships between data points.
•   Infographic
•   Creating informative and visually appealing infographics in Power BI.
•   Play Axis.
•   Using the Play Axis feature for dynamic data exploration.
•   Scroller.
•   Creating data-driven scroller visuals for dynamic presentations.
•   Sunburst Chart.
•   Constructing sunburst charts to display hierarchical data.
•   Histogram
•   Utilizing histograms for data distribution analysis.

Module 9:Objects and Actions in Power BI

•   Inserting Images
•   After discuss with ruchira mam 17 pages put in to draft
•   Inserting Text
•   Incorporating text elements to provide context and information.
•   Inserting Shapes
•   Creating and formatting shapes for design and highlighting.
•   Inserting Buttons
•   Adding interactive buttons for navigation and user interaction.
•   Action - Web URL
•   Configuring actions to open web URLs when interacting with visuals.
•   Action - Page Navigation
•   Using actions to navigate between report pages.
•   Action - Back.
•   Implementing the "Back" action for quick navigation.
•   Action - Bookmark.
•   Utilizing actions with bookmarks for saving and restoring report states.
•   Action - Drill Through
•   Setting up actions for drill-through interactions in your report.

Module 10:Text Functions in Power Query

•   Merge
•   Combining and merging text data from multiple columns.
•   Split and Trim
•   Splitting text values and trimming extra spaces for data cleaning.
•   UPPER, LOWER, and PROPER
•   Changing text case using uppercase, lowercase, and proper case functions.
•   Add Suffix and Prefix
•   Adding prefixes and suffixes to text values.
•   LEFT, RIGHT, and MID
•   Extracting text from the left, right, and middle of a text string.
•   Extract Text with Delimiters
•   Using delimiters to extract specific portions of text.

Module 11:Date Functions in Power Query

•   YEAR, QUARTER, MONTH, DAY
•   Extracting the year, quarter, month, and day from date values.
•   Difference Between Dates, Earliest, and Latest
•   Calculating the difference between dates and finding the earliest and latest dates.
•   Name of Day and Name of Month
•   Retrieving the name of the day and month from date values.
•   Day of Week, Month, Year, and Week of Month/Year
•   Determining the day of the week, month, year, and the week of the month/year.
•   LEFT, RIGHT, and MID
•   Extracting text from the left, right, and middle of a text string.
•   Extracting Date from Date and Time
•   Isolating the date portion from date and time values.
•   Calculating Age in 2 Button Clicks
•   Simplifying age calculation in Power Query.
•   Day of Year, Quarter, Month of Birth Date.
•   Determining on which day of the year, quarter, and month your birth date falls.

Module 12:Arithmetic Operations And Number Functions

•   Importance of number functions in data transformation
•   Basic Arithmetic Operations in Power Query
•   Adding numbers in Power Query
•   Subtracting numbers in Power Query
•   Multiplying numbers in Power Query
•   Dividing numbers in Power Query
•   Working with percentages in Power Query
•   Calculating the percentage of a total
•   Using the modulo function for remainder calculations
•   Rounding numbers to specific decimal places
•   Conditional Number Functions
•   Using IF statements for conditional calculations
•   Determining if a number is even
•   Determining if a number is odd
•   Calculating the sign of a number (positive, negative, or zero)

Module 13:Introduction to Data Appending in Power BI

•   Overview of data appending in Power BI
•   Understanding the need for combining data from multiple sources
•   Differentiating between data appending and data merging
•   Merging Tables and Sheets in Power Query
•   Techniques for merging tables/sheets within a single file
•   Using Power Query to perform table joins
•   Exploring the types of table joins (inner, outer, left, right)
•   Handling common issues and errors in table merging
•   Merging Data from Multiple Excel Files/Workbooks
•   Merging data from multiple Excel workbooks using Power Query
•   Structuring data for effective merging
•   Handling scenarios where workbooks have different structures
•   Creating robust and automated data integration processes
•   Merging Data from Different Data Sources
•   Merging data from various data sources in Power Query
•   Data transformation during the merge process
•   Ensuring data consistency and quality
•   Merging Data with Multiple Matching Columns or Criteria
•   Dealing with data merge scenarios involving multiple matching columns or criteria
•   Applying advanced merge techniques in Power Query
•   Strategies for merging data with complex relationships
•   Handling hierarchical or multi-level data relationships

Module 14:Introduction to Column Creation In Power BI

•   Overview of the importance of custom columns
•   Understanding the need for creating custom columns
•   Differentiating between calculated columns and calculated tables
•   Creating Columns from Examples
•   Introduction to "Column from Examples" feature
•   Splitting text using "Column from Examples"
•   Merging text using "Column from Examples
•   Generating data columns with custom rules
•   Creating alphanumeric data columns
•   Conditional Columns in Power BI
•   Introduction to conditional columns
•   Creating a conditional column based on a single column
•   Setting up conditional columns using IF statements
•   Advanced Conditional Columns
•   Creating conditional columns based on two column values
•   Complex conditional column scenarios with multiple criteria
•   Conditional columns involving comparisons of two column values
•   Conditional columns for date-related calculations

Module 15:Introduction to DAX Functions In Power BI

•   Overview of DAX (Data Analysis Expressions)
•   Understanding the role of DAX in Power BI
•   Differences between measures and calculated columns
•   Defining relationships in Power BI data models
•   Basic DAX Functions and Measures
•   Creating new measures using the SUM function
•   Formatting measures for better visualization
•   Introduction to time and date functions in DAX
•   Using IF conditions in DAX for calculations
•   Aggregation Functions and Advanced DAX Concepts
•   DISTINCTCOUNT function for counting unique values
•   Working with MIN, MAX, and AVERAGE functions
•   Understanding and using the CALCULATE function in DAX
•   Adding calculated columns with DAX expressions
•   Advanced DAX Techniques
•   Exploring alternate syntax for the CALCULATE function
•   Introduction to variables in DAX for complex calculations
•   Using OR conditions in DAX with CALCULATE for more sophisticated filtering
•   Practical examples and case studies to illustrate DAX functions

Module 16:M Language In Power Query

•   Introduction to M Language and Basic Functions
•   Overview of M Language in Power Query
•   Introduction to M Functions: DATE (ISIN)
•   Introduction to M Functions: DATE (ADD and SUBTRACT)
•   Advanced M Date Functions
•   Advanced M Functions: TEXT (BASIC)
•   Writing M Code in Power BI
•   Understanding the Structure of M Code
•   Writing a Small M Code in Power BI
•   Tips and Best Practices for Writing Efficient M Code
•   Tricks and Resources for M Language Mastery
•   Trick to Get Help for All 900 M Functions
•   Overview of Advanced M Concepts and Resources for Further Learning

Module 17:Important Topics Of Power Query

•   Data Import and Basic Transformation
•   Overview of importing data into Power BI using Power Query.
•   Introduction to basic transformations like renaming columns, changing data types, and filtering rows.
•   Fill Down and Fill Up
•   Explanation of the Fill Down and Fill Up functionalities in Power Query.
•   Demonstration of scenarios where Fill Down and Fill Up are useful.
•   Grouping and Aggregation
•   Overview of Grouping feature in Power Query.
•   Explanation of how to group data based on one or more columns.
•   Examples of aggregation functions like sum, count, average, etc.
•   Transpose and Unpivot
•   Introduction to Transpose and Unpivot operations in Power Query.
•   Explanation of how Transpose changes rows to columns and vice versa.
•   Data Types in Power Query
•   Overview of common data types available in Power Query (Text, Number, Date, etc.).
•   Replace Errors and Values
•   Introduction to replacing errors and values in Power Query.
•   keep Rows and Remove Rows
•   Overview of Keep Rows and Remove Rows operations.
•   Explanation of filtering rows based on criteria.
•   Explanation of adding and removing columns in Power Query.
•   Introduction to the Go To Columns feature for easy navigation.

Module 18:

•   Data Import and Basic Transformation
•   Overview of importing data into Power BI using Power Query.
•   Introduction to basic transformations like renaming columns, changing data types, and filtering rows.
•   Fill Down and Fill Up
•   Explanation of the Fill Down and Fill Up functionalities in Power Query.
•   Demonstration of scenarios where Fill Down and Fill Up are useful.
•   Grouping and Aggregation
•   Overview of Grouping feature in Power Query.
•   Explanation of how to group data based on one or more columns.
•   Examples of aggregation functions like sum, count, average, etc.
•   Transpose and Unpivot
•   Introduction to Transpose and Unpivot operations in Power Query.
•   Explanation of how Transpose changes rows to columns and vice versa.
•   Data Types in Power Query
•   Overview of common data types available in Power Query (Text, Number, Date, etc.).
•   Replace Errors and Values
•   Introduction to replacing errors and values in Power Query.
•   keep Rows and Remove Rows
•   Overview of Keep Rows and Remove Rows operations.
•   Explanation of filtering rows based on criteria.
•   Explanation of adding and removing columns in Power Query.
•   Introduction to the Go To Columns feature for easy navigation.

Module 19:Power Bi Service Intro

•   Creating A Superstore Report
•   Create An Account On Power Bi Service
•   Publish Report To Powerbi Service Account
•   Export (Ppt, Pdf, Pbix) Report And Share
•   Comment, Share And Subscribe To Report
•   Create Dashboard In Powerbi Services
•   Problems In Powerbi Dashboard And Its Solution
•   Automatic Refresh - Data Gateway
•   Create Report Directly In Power Bi Services

Module 1: Introduction to Machine Learning

•   Explore the basics of machine learning, including its applications in data science and various industries.

Module 2: Supervised Learning

•   Understand supervised learning algorithms such as regression and classification, and how they are used to make predictions based on labeled data.

Module 3: Unsupervised Learning

•   Learn about unsupervised learning techniques like clustering and dimensionality reduction, used for discovering patterns and structures in unlabeled data.

Module 4: Model Evaluation and Validation

•   Gain insights into techniques for evaluating and validating machine learning models to ensure their accuracy and reliability.

Module 5: Advanced Topics

•   Delve into advanced topics such as ensemble methods, deep learning, and reinforcement learning, and their applications in solving complex real-world problems.

Module 1: Introduction to Machine Learning

•   Introduction to Artificial Intelligence.
•   History of Arificial Intelligence.
•   Future and Market Trends in Artificial Intelligence.
•   Neural Network and Perceptron.
•   Understanding Feedforward Networks.
•   Exploring Backpropagation.
•   Understanding Sensor Processing.
•   Studying Neural Elements.

Module1 : Introduction to R programming

•   Understand critical programming language concepts
•   This module starts from the basics of R programming like datatypes and functions.
•   You will also learn how to apply the ‘join’ function in SQL.

Module 2: Data Manipulation in R

•   In this module, we start with a sample of a dirty data set and perform Data Cleaning on it, resulting in a data set, which is ready for any analysis.
•   Thus using and exploring the popular functions required to clean data in R.
•   Character set
•   Comments
•   Punctuators
•   Identifiers

Module 3: Data Import techniques in R

•   This module tells you about the versatility and robustness of R which can take-up data in a variety of formats, be it from a csv file to the data scraped from a website.
•   This module teaches you various data importing techniques in R

Module 4: Exploratory Data Analysis

•   In this module, you will learn that exploratory data analysis is an important step in the analysis.

Module 5: Overview of Machine Learning techniques

•   This module touches the base Statistics, Machine learning techniques used in the Industry and will cover case studies.