Masters in Generative AI

Presenting and Managing Data in Excel

• Basic Understanding Menu and Toolbar
• Introduction to different category of functions
• Creation of Excel Sheet Data
• Range Name, Format Painter
• Conditional Formatting, Wrap Text, Merge & Centre
• Sort, Filter, Advance Filter
• Different type of Chart Creations
• Auditing, (Trace Precedents, Trace Dependents) Print Area
• Data Validations, Consolidate, Subtotal
• What if Analysis (Data Table, Goal Seek, Scenario)
• Solver, Freeze Panes
• Various Simple Functions in Excel (Sum, Average, Max, Min)
• Real Life Assignment work

Manage Workbook Options and Settings

• Manage workbook
  • Save a workbook as a template,
  • copy macros between workbooks,
  • reference data in another workbook,
  • reference data by using structured references,
  • enable macros in a workbook,
  • display hidden ribbon tabs
• Manage workbook review
  • Restrict editing,
  • protect a worksheet
  • configure formula calculation options
  • protect workbook structure
  • manage workbook versions
  • encrypt a workbook with a password

Apply Custom Data Formats and Layouts

• Apply custom data formats and validation
  • Create custom number formats
  • populate cells by using advanced Fill Series options
  • configure data validation
• Apply advanced conditional formatting and filtering
  • Create custom conditional formatting rules
  • create conditional formatting rules that use formulas
  • manage conditional formatting rules
• Create and modify custom workbook elements
  • Create custom color formats,
  • create and modify cell styles,
  • create and modify custom themes,
  • create and modify simple macros
  • insert and configure form controls
• Prepare a workbook for internationalization
  • Display data in multiple international formats
  • apply international currency formats,
  • manage multiple options for Body and Heading fonts

Create Advanced Formulas

• Apply functions in formulas
  • Perform logical operations by using AND, OR, and NOT functions;
  • perform logical operations by using nested functions
  • perform statistical operations by using SUMIFS, AVERAGEIFS, COUNTIFS
  • functions
• Look up data by using functions
  • Look up data by using the VLOOKUP function,
  • look up data by using the HLOOKUP function,
  • look up data by using the MATCH function,
  • look up data by using the INDEX function
• Apply advanced date and time functions
  • Reference the date and time by using the NOW and TODAY functions,
  • serialize numbers by using date and time functions
• Perform data analysis and business intelligence
  • Reference the date and time by using the NOW and TODAY functions
  • import, transform, combine, display, and connect to data
  • consolidate data
  • perform what-if analysis by using Goal Seek and Scenario Manager
  • use cube functions to get data out of the Excel data model
  • calculate data by using financial functions
• Troubleshoot formulas
  • Trace precedence and dependence
  • monitor cells and formulas by using the Watch Window
  • validate formulas by using error checking rules,
  • Evaluate formulas
• Define named ranges and objects
  • Name cells,
  • name data ranges,
  • name tables,
  • manage named ranges and objects
• Module 5: Create Advanced Charts and Tables
• Create advanced charts
  • Add trendlines to charts,
  • create dual-axis charts,
  • save a chart as a template
• Create and manage PivotTables
  • Create PivotTables,
  • modify field selections and options,
  • create slicers,
  • group PivotTable data,
  • reference data in a PivotTable by using the GETPIVOTDATA function,
  • add calculated fields,
  • format data
• Create and manage PivotCharts
  • Create PivotCharts,
  • manipulate options in existing PivotCharts,
  • apply styles to PivotCharts,
  • drill down into PivotChart details

MIS Reporting and Dashboards (Any 03 Dashboards)

• Dashboard Background
• Dashboard Elements
• Interactive Dashboards
• Type of Reporting in India
• Reporting Analyst
• Indian Print Media Reporting
• Audit Report
• Accounting MIS Reports
• HR MIS Reports
• MIS Report Preparation Supplier, Exporter
• Data Analysis
• Costing Budgeting Mis Reporting
• MIS Reporting for Manufacturing Company
• MIS Reporting for Store and Billing
• Product Performance Report
• Member Performance Report
• Customer-Wise Sales Report
• Collections Report
• Channel Stock Report
• Prospect Analysis Report
• Calling Reports
• Expenses Report
• Stock Controller MIS Reporting
• Inventory Statement
• Payroll Report
• Salary Slip
• Loan Assumption Sheet
• Invoice Creation

Macros and VBA

• What is a Macro
• Recording a Macro.
• Different components of a macro.
• What is VBA and how to write macros in VBA.
  • Writing a simple macro
  • Apply arithmetic operations on two cells using macros.
  • How to align the text using macros.
  • How to change the background color of the cells using macros.
  • How to change the border color and style of the cells using macros.
  • Use cell referencing using macros.
  • How to copy the data from one cell and paste it into another.
  • How to change the font color of the text in a cell using macros.

Incorporating AI Into Excel

• Recognize patterns and extract data from images with Excel AI tools
• Find and match patterns in datasets using Flash Fill
• Apply AI algorithms to transform data in Power Query
• Review AI recommendations for charts and pivot tables
• Analyze data and make predictions using the Forecasting tool
• Automate data analysis using the Analyze Data tool

Combining ChatGPT With Microsoft Excel

• Leverage the power of ChatGPT to make your workday more productive
• Evaluate specific data analysis needs using ChatGPT prompts
• Solve everyday Excel challenges with ChatGPT
• Configure the ChatGPT API to add a connection to Excel
• Create advanced formulas with the Excel Labs feature

SQL Fundamental

• Introduction & Software Installation
  • Overview of Oracle Database
  • Introduction to SQL and its Development Environments
  • Installing Oracle
  • Installing Java SDK
  • Installing SQL Developer Client
• Overview of RDBMS Concepts And Terminologies
  • What is RDBMS
  • Features of RDBMS
  • Advantages of RDBMS
  • Database Normalization
  • SQL Constraints
  • SQL RDBMS Concept
  • Types of keys in DBMS
• Database Design and Basics
  • Understanding of Database Terms
  • What is Good Database Design
  • The Design Process
  • Determining the purpose of your Database
  • Finding and Organizing the required Information
  • Dividing the Information into Tables
  • Turning Information Items into Columns
  • Specifying Primary Keys
  • Creating the Table Relationships
  • Refining the Design
  • Applying the Normalization Rules
• Database Security Concepts
  • The Scope of Database Security
  • Overview | Threats to the Database | Principles of Database Security
  • Security Models
  • Access Control | Authentication and Authorisation | Authentication | Authorisation | Access Philosophies and Management
  • Database Security Issues
  • Access to Key Fields | Access to Surrogate Information | Problems with Data | Extraction | Access Control in SQL | Discretionary Security in SQL | Schema | Level | Authentication | Table Level | SQL System Tables | Mandatory Security in SQL | Data Protection
• Database Performance
  • Optimize Queries
  • Create Optimal Indexes
  • Memory Allocation
  • Data Defragmentation
• Retrieve Data Using The Sql Select Statement
  • List the Capabilities Of Sql Select Statements
  • Generate a Report Of Data From the Output Of a Basic Select Statement
  • Use Arithmetic Expressions and Null Values In the Select Statement
  • Invoke Column Aliases
  • Concatenation Operator, Literal Character Strings, Alternative Quote Operator, and the
  • Distinct Keyword
  • Display the Table Structure Using the Describe Command
• Restricted And Sorted Data
  • Write Queries With a Where Clause to Limit the Output Retrieved
  • Describe the Comparison Operators and Logical Operators
  • Describe the Rules Of Precedence For Comparison and Logical Operators
  • Usage Of Character String Literals In the Where Clause
  • Write Queries With an Order By Clause
  • Sort the Output In Descending and Ascending Order
  • Substitution Variables
• Usage Of Single-Row Functions To Customize Output
  • List the Differences Between Single Row and Multiple Row Functions
  • Manipulate Strings Using Character Functions
  • Manipulate Numbers With the ROUND, TRUNC, and MOD Functions
  • Perform Arithmetic With Date Data
  • Manipulate Dates With the DATE Functions
• Conversion Functions And Conditional Expressions
  • Describe Implicit and Explicit Data Type Conversion
  • Describe The TO_CHAR, TO_NUMBER, And TO_DATE Conversion Functions
  • Nesting Multiple Functions
  • Apply the NVL, NULLIF, and COALESCE Functions to Data
  • Usage Of Conditional IF THEN ELSE Logic In a SELECT Statement
• Aggregated Data Using The Group Functions
  • Usage Of The Aggregation Functions In SELECT Statements To Produce Meaningful
  • Reports
  • Describe the AVG, SUM, MIN, and MAX Function
  • How to Handle Null Values In a Group Function
  • Divide The Data In Groups By Using The GROUP BY Clause
  • Exclude Groups Of Date By Using The HAVING Clause
• Display Data From Multiple Tables
  • Write SELECT Statements To Access Data From More Than One Table
  • Join Tables Using SQL:1999 Syntax
  • View Data That Does Not Meet a Join Condition By Using Outer Joins
  • Join A Table To Itself By Using a Self-Join
  • Create Cross Joins
• Usage Of Subqueries To Solve Queries
  • Use a Subquery To Solve a Problem
  • Single-Row Subqueries
  • Group Functions In A Subquery
  • Multiple-Row Subqueries
  • Use The ANY and ALL Operator In Multiple-Row Subqueries
  • Use The EXISTS Operator
• SET Operators
  • Describe The SET Operators
  • Use A SET Operator To Combine Multiple Queries Into a Single Query
  • Describe The UNION, UNION ALL, INTERSECT, and MINUS Operators
  • Use The ORDER BY Clause In Set Operations
• Data Manipulation
  • Add New Rows To a Table
  • Change The Data In a Table
  • Use The DELETE and TRUNCATE Statements
  • How To Save and Discard Changes With The COMMIT and ROLLBACK Statements
  • Implement Read Consistency
  • Describe The FOR UPDATE Clause
• DDL Statements To Create And Manage Tables
  • Categorize Database Objects
  • Create Tables
  • Describe The Data Types
  • Understand Constraints
  • Create a Table Using A Subquery
  • How To Alter a Table
  • How To Drop a Table
• Other Schema Objects
  • Create, Modify, And Retrieve Data From a View
  • Perform Data Manipulation Language (DML) Operations On a View
  • How to Drop a View
  • Create, Use, and Modify a Sequence
  • Create and Drop Indexes
  • Create and Drop Synonyms

Advance SQL

• Manipulating Data
  • Default Values for Columns
  • Virtual Columns
  • Arithmetic Calculations on NULL Values
  • Multi table Insert's
  • Merge the Data
• Analytical Functions
  • Analytical Functions Introduction
  • Getting the Cumulative Sum of Sales
  • Displaying Sales as a Percentage of Total Sales
  • Ranking your Data
  • Performing Top N Analysis
  • Dividing your Data into Bands
  • LAG and LEAD Function Examples
  • Analyzing Sales Growth Across Time
  • Analytical Functions Recap
• Transforming the Data
  • Row Level Data to Column Level using CASE statement
  • Row Level Data to Column Level using PIVOT
  • Row Level Data to Column Level using LISTAGG
  • Column Level Data to Row Level using UNION
  • Column Level Data to Row Level using UNPIVOT
• Hierarchical Queries
  • Hierarchical Queries Introduction
  • Connect By Clause
  • Creating the Hierarchy Tree
  • Sorting the Hierarchy Tree
  • CONNECT_BY_ROOT Unary Operator
  • SYS_CONNECT_BY_PATH Function
  • CONNECT BY for Number Generation
• Regular Expressions
  • Regular Expressions Introduction
  • Meta Characters . and +
  • Meta Characters and *
  • Interval Operator to Match the Number of Occurrences
  • Matching the Characters in a List
  • Combine Multiple Expressions Using |
  • Check for an Expression in the Beginning or End of a String
  • Search for Meta Characters by Placing a Escape Character
• Materialized Views
  • Materialized Views Introduction
  • Materialized Views Creation Options
  • Materialized Views with ON COMMIT Option
  • Materialized Views with ON DEMAND Option
  • Materialized Views with REFRESH FAST Option
  • Timing the Refresh

Introduction to Power BI

• Overview of BI concepts
• Why we need BI
• Introduction to SSBI
• SSBI Tools
• Why Power BI
• What is Power BI
• Building Blocks of Power BI
• Getting started with Power BI Desktop
• Get Power BI Tools
• Introduction to Tools and Terminology
• Dashboard in Minutes
• Interacting with your Dashboards
• Sharing Dashboards and Reports

Power BI Desktop

• Power BI Desktop
• Extracting data from various sources
• Workspaces in Power BI

Power BI Data Transformation

• Data Transformation
• Query Editor
• Connecting Power BI Desktop to our Data Sources
• Editing Rows
• Understanding Append Queries
• Editing Columns
• Replacing Values
• Formatting Data
• Pivoting and Unpivoting Columns
• Splitting Columns
• Creating a New Group for our Queries
• Introducing the Star Schema
• Duplicating and Referencing Queries
• Creating the Dimension Tables
• Entering Data Manually
• Merging Queries
• Finishing the Dimension Table
• Introducing the another DimensionTable
• Creating an Index Column
• Duplicating Columns and Extracting Information
• Creating Conditional Columns
• Creating the FACT Table
• Performing Basic Mathematical Operations
• Improving Performance and Loading Data into the Data Model

Modelling with Power BI

• Introduction to Modelling
• Modelling Data
• Manage Data Relationship
• Optimize Data Models
• Cardinality and Cross Filtering
• Default Summarization & Sort by
• Creating Calculated Columns
• Creating Measures & Quick Measures

Data Analysis Expressions (DAX)

• What is DAX
• Data Types in DAX
• Calculation Types
• Syntax, Functions, Context Options
• DAX Functions
  • Date and Time
  • Time Intelligence
  • Information
  • Logical
  • Mathematical
  • Statistical
  • Text and Aggregate
• Measures in DAX
• Measures and Calculated Columns
• ROW Context and Filter Context in DAX
• Operators in DAX - Real-time Usage
• Quick Measures in DAX - Auto validations
• In-Memory Processing DAX Performance

Power BI Desktop Visualisations

• How to use Visual in Power BI
• What Are Custom Visuals
• Creating Visualisations and Colour Formatting
• Setting Sort Order
• Scatter & Bubble Charts & Play Axis
• Tooltips and Slicers, Timeline Slicers & Sync Slicers
• Cross Filtering and Highlighting
• Visual, Page and Report Level Filters
• Drill Down/Up
• Hierarchies and Reference/Constant Lines
• Tables, Matrices & Conditional Formatting
• KPI's, Cards & Gauges
• Map Visualizations
• Custom Visuals
• Managing and Arranging
• Drill through and Custom Report Themes
• Grouping and Binning and Selection Pane, Bookmarks & Buttons
• Data Binding and Power BI Report Server

Introduction to Power BI Dashboard and Data Insights

• Why Dashboard and Dashboard vs Reports
• Creating Dashboards
• Conguring a Dashboard Dashboard Tiles, Pinning Tiles
• Power BI Q&A
• Quick Insights in Power BI

Direct Connectivity

• Custom Data Gateways
• Exploring live connections to data with Power BI
• Connecting directly to SQL Server
• Connectivity with CSV & Text Files
• Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
• Content packs
• Update content packs

Publishing and Sharing

• Introduction and Sharing Options Overview
• Publish from Power BI Desktop and Publish to Web
• Share Dashboard with Power BI Service
• Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
• Print or Save as PDF and Row Level Security (Power BI Pro)
• Export Data from a Visualization
• Export to PowerPoint and Sharing Options Summary

Refreshing Datasets

• Understanding Data Refresh
• Personal Gateway (Power BI Pro and 64-bit Windows)
• Replacing a Dataset and Troubleshooting Refreshing

Introduction to Data Preparation using Tableau

• Data Visualization
• Business Intelligence tools
• Introduction to Tableau
• Tableau Architecture
• Tableau Server Architecture
• VizQL Fundamentals
• Introduction to Tableau Prep
• Tableau Prep Builder User Interface
• Data Preparation techniques using Tableau Prep Builder tool

Data Connection with Tableau Desktop

• Features of Tableau Desktop
• Connect to data from File and Database
• Types of Connections
• Joins and Unions
• Data Blending
• Tableau Desktop User Interface

Basic Visual Analytics

• Visual Analytics
• Basic Charts Bar Chart, Line Chart, and Pie Chart
• Hierarchies
• Data Granularity
• Highlighting
• Sorting
• Filtering
• Grouping
• Sets

Calculations in Tableau

• Types of Calculations
• Built-in Functions (Number, String, Date, Logical and Aggregate)
• Operators and Syntax Conventions
• Table Calculations
• Level of Detail (LOD) Calculations
• Using R within Tableau for Calculations

Advanced Visual Analytics

• Parameters
• Tool tips
• Trend lines
• Reference lines
• Forecasting
• Clustering

Level of Detail (LOD) Expressions in Tableau

• Count Customer by Order
• Profit per Business Day
• Comparative Sales
• Profit Vs Target
• Finding the second order date
• Cohort Analysis

Geographic Visualizations in Tableau

• Introduction to Geographic Visualizations
• Manually assigning Geographical Locations
• Types of Maps
• Spatial Files
• Custom Geocoding
• Polygon Maps
• Web Map Services
• Background Images

Advanced charts in Tableau

• Box and Whisker?s Plot
• Bullet Chart
• Bar in Bar Chart
• Gantt Chart
• Waterfall Chart
• Pareto Chart
• Control Chart
• Funnel Chart
• Bump Chart
• Step and Jump Lines
• Word Cloud
• Donut Chart

Dashboards and Stories

• Introduction to Dashboards
• The Dashboard Interface
• Dashboard Objects
• Building a Dashboard
• Dashboard Layouts and Formatting
• Interactive Dashboards with actions
• Designing Dashboards for devices
• Story Points

Get Industry Ready

• Tableau Tips and Tricks
• Choosing the right type of Chart
• Format Style
• Data Visualization best practices

Exploring Tableau Online

• Publishing Workbooks to Tableau Online
• Interacting with Content on Tableau Online
• Data Management through Tableau Catalog
• AI-Powered features in Tableau Online (Ask Data and Explain Data)
• Understand Scheduling
• Managing Permissions on Tableau Online
• Data Security with Filters in Tableau Online

Introduction To Python

• Installation and Working with Python
• Understanding Python variables
• Python basic Operators
• Understanding the Python blocks.

Python Keyword and Identiers

• Python Comments, Multiline Comments.
• Python Indentation
• Understating the concepts of Operators
• Arithmetic
• Relational
• Logical
• Assignment
• Membership
• Identity

Introduction To Variables

• Variables, expression condition and function
• Global and Local Variables in Python
• Packing and Unpacking Arguments
• Type Casting in Python
• Byte objects vs. string in Python
• Variable Scope

Python Data Type

• Declaring and using Numeric data types
• Using string data type and string operations
• Understanding Non-numeric data types
• Understanding the concept of Casting and Boolean.
• Strings
• List
• Tuples
• Dictionary
• Sets

Control Structure & Flow

• Statements ? if, else, elif
• How to use nested IF and Else in Python
• Loops
• Loops and Control Statements.
• Jumping Statements ? Break, Continue, pass
• Looping techniques in Python
• How to use Range function in Loop
• Programs for printing Patterns in Python
• How to use if and else with Loop
• Use of Switch Function in Loop
• Elegant way of Python Iteration
• Generator in Python
• How to use nested Loop in Python
• Use If and Else in for and While Loop
• Examples of Looping with Break and Continue Statement
• How to use IN or NOT IN keyword in Python Loop.

List

• What is List.
• List Creation
• List Length
• List Append
• List Insert
• List Remove
• List Append & Extend using ?+? and Keyword
• List Delete
• List related Keyword in Python
• List Reverse
• List Sorting
• List having Multiple Reference
• String Split to create a List
• List Indexing
• List Slicing
• List count and Looping
• List Comprehension and Nested Comprehension

Tuple

• What is Tuple
• Tuple Creation
• Accessing Elements in Tuple
• Changing a Tuple
• Tuple Deletion
• Tuple Count
• Tuple Index
• Tuple Membership
• TupleBuilt in Function (Length, Sort)

Dictionary

• Dict Creation
• Dict Access (Accessing Dict Values)
• Dict Get Method
• Dict Add or Modify Elements
• Dict Copy
• Dict From Keys.
• Dict Items
• Dict Keys (Updating, Removing and Iterating)
• Dict Values
• Dict Comprehension
• Default Dictionaries
• Ordered Dictionaries
• Looping Dictionaries
• Dict useful methods (Pop, Pop Item, Str , Update etc.)

Sets

• What is Set
• Set Creation
• Add element to a Set
• Remove elements from a Set
• PythonSet Operations
• Frozen Sets

Strings

• What is Set
• Set Creation
• Add element to a Set
• Remove elements from a Set
• PythonSet Operations

Python Function, Modules and Packages

• Python Syntax
• Function Call
• Return Statement
• Arguments in a function ? Required, Default, Positional, Variable-length
• Write an Empty Function in Python ?pass statement.
• Lamda/ Anonymous Function
• *args and **kwargs
• Help function in Python
• Scope and Life Time of Variable in Python Function
• Nested Loop in Python Function
• Recursive Function and Its Advantage and Disadvantage
• Organizing python codes using functions
• Organizing python projects into modules
• Importing own module as well as external modules
• Understanding Packages
• Random functions in python
• Programming using functions, modules & external packages
• Map, Filter and Reduce function with Lambda Function
• More example of Python Function

Decorator, Generator and Iterator

• Creation and working of decorator
• Idea and practical example of generator, use of generator
• Concept and working of Iterator

Python Exception Handling

• Python Errors and Built-in-Exceptions
• Exception handing Try, Except and Finally
• Catching Exceptions in Python
• Catching Specic Exception in Python
• Raising Exception
• Try and Finally

Python File Handling

• Opening a File
• Python File Modes
• Closing File
• Writing to a File
• Reading from a File
• Renaming and Deleting Files in Python
• Python Directory and File Management
• List Directories and Files
• Making New Directory
• Changing Directory

Memory management using python

• Threading, Multi-threading
• Memory management concept of python
• working of Multi tasking system
• Different os function with thread

Python Database Interaction

• SQL Database connection using
• Creating and searching tables
• Reading and Storing cong information on database
• Programming using database connections

Reading an excel

• Working With Excel
• Reading an excel le using Python
• Writing to an excel sheet using Python
• Python| Reading an excel le
• Python | Writing an excel le
• Adjusting Rows and Column using Python
• ArithmeticOperation in Excel le.
• Play with Workbook, Sheets and Cells in Excel using Python
• Creating and Removing Sheets
• Formatting the Excel File Data
• More example of Python Function

Complete Understanding of OS Module of Python

• Check Dirs. (exist or not)
• How to split path and extension
• How to get user prole detail
• Get the path of Desktop, Documents, Downloads etc.
• Handle the File System Organization using OS
• How to get any les and folder?s details using OS

Introduction to Machine Learning

• What is Machine Learning
• Machine Learning Use-Cases
• Machine Learning Process Flow
• Machine Learning Categories

Supervised Learning

• Classification and Regression
• Where we use classification model and where we use regression
• Regression Algorithms and its types

Regression Algorithm

• Logistic Regression
• Evaluation Matrix of Regression Algorithm

Classification Algorithm

• Implementing KNN
• Implementing Na?ve Bayes Classifier
• Implementation and Introduction to Decision Tree using CARTand ID3
• Introduction to Ensemble Learning
• Random Forest algorithm using bagging and boosting
• Evaluation Matrix of classification algorithms (confusion matrix, r2score, Accuracy,f1-score,recall and precision

Optimization Algorithm

• Hyperparameter Optimization
• Grid Search vs. Random Search

Dimensionality Reduction

• Introduction to Dimensionality
• Why Dimensionality Reduction
• PCA
• Factor Analysis
• Scaling dimensional model
• LDA
• ICA

Unsupervised Learning

• What is Clustering & its Use Cases
• What is K-means Clustering
• How does the K-means algorithm works
• How to do optimal clustering
• What is Hierarchical Clustering
• How does Hierarchical Clustering work

Association Rules Mining and Recommendation Systems

• What are Association Rules
• Association Rule Parameters
• Calculating Association Rule Parameters
• Recommendation Engines
• How do Recommendation Engines work
• Collaborative Filtering
• Content-Based Filtering
• Association Algorithms
• Implementation of Apriori Association Algorithm

Reinforcement Learning

• What is Reinforcement Learning
• Why Reinforcement Learning
• Elements of Reinforcement Learning
• Exploration vs. Exploitation dilemma
• Epsilon Greedy Algorithm
• Markov Decision Process (MDP)
• Q values and V values
• Q ? Learning
• Values

Time Series Analysis

• What is Time Series Analysis
• Importance of TSA
• Components of TSA

Model Selection and Boosting

• What is Model Selection
• Need for Model Selection
• Cross Validation
• What is Boosting
• How do Boosting Algorithms work
• Types of Boosting Algorithms
• Adaptive Boosting

Introduction to Text Mining and NLP

• Overview of Text Mining
• Need of Text Mining
• Natural Language Processing (NLP) in Text Mining
• Applications of Text Mining
• OS Module
• Reading, Writing to text and word files
• Setting the NLTK Environment
• Accessing the NLTK Corpora

Extracting, Cleaning and Preprocessing Text

• Tokenization
• Frequency Distribution
• Different Types of Tokenizers
• Bigrams, Trigrams & Ngrams
• Stemming
• Lemmatization
• Stopwords
• POS Tagging
• Named Entity Recognition

Analyzing Sentence Structure

• Syntax Trees
• Chunking
• Chinking
• Context Free Grammars (CFG)
• Automating Text Paraphrasing

Text Classification - I

• Machine Learning: Brush Up
• Bag of Words
• Count Vectorizer
• Term Frequency (TF)
• Inverse Document Frequency (IDF)

Getting Started with TensorFlow 2.0

• Introduction to TensorFlow 2.x
• Installing TensorFlow 2.x
• Defining Sequence model layers
• Activation Function
• Layer Types
• Model Compilation
• Model Optimizer
• Model Loss Function
• Model Training
• Digit Classification using Simple Neural Network in TensorFlow 2.x
• Improving the model
• Adding Hidden Layer
• Adding Dropout
• Using Adam Optimizer

Introduction to Deep Learning

• What is Deep Learning
• Curse of Dimensionality
• Machine Learning vs. Deep Learning
• Use cases of Deep Learning
• Human Brain vs. Neural Network
• What is Perceptron
• Learning Rate
• Epoch
• Batch Size
• Activation Function
• Single Layer Perceptron

Neural Networks

• What is NN
• Types of NN
• Creation of simple neural network using tensorflow

Convolution Neural Network

• Image Classification Example
• What is Convolution
• Convolutional Layer Network
• Convolutional Layer
• Filtering
• ReLU Layer
• Pooling
• Data Flattening
• Fully Connected Layer
• Predicting a cat or a dog
• Saving and Loading a Model
• Face Detection using OpenCV

Image Processing and Computer Vision

• Introduction to Vision
• Importance of Image Processing
• Image Processing Challenges ? Interclass Variation, ViewPoint Variation, Illumination, Background Clutter, Occlusion & Number of Large Categories
• Introduction to Image ? Image Transformation, Image Processing Operations & Simple Point Operations
• Noise Reduction ? Moving Average & 2D Moving Average
• Image Filtering ? Linear & Gaussian Filtering
• Disadvantage of Correlation Filter
• Introduction to Convolution
• Boundary Effects ? Zero, Wrap, Clamp & Mirror
• Image Sharpening
• Template Matching
• Edge Detection ? Image filtering, Origin of Edges, Edges in images as Functions, Sobel Edge Detector
• Effect of Noise
• Laplacian Filter
• Smoothing with Gaussian
• LOG Filter ? Blob Detection
• Noise ? Reduction using Salt & Pepper Noise using Gaussian Filter
• Nonlinear Filters
• Bilateral Filters
• Canny Edge Detector - Non Maximum Suppression, Hysteresis Thresholding
• Image Sampling & Interpolation ? Image Sub Sampling, Image Aliasing, Nyquist Limit, Wagon Wheel Effect, Down Sampling with Gaussian Filter, Image Pyramid, Image Up Sampling
• Image Interpolation ? Nearest Neighbour Interpolation, Linear Interpolation, Bilinear Interpolation & Cubic Interpolation
• Introduction to the dnn module
  • Deep Learning Deployment Toolkit
  • Use of DLDT with OpenCV4.0
• OpenVINO Toolkit
  • Introduction
  • Model Optimization of pre-trained models
  • Inference Engine and Deployment process

Regional CNN

• Regional-CNN
• Selective Search Algorithm
• Bounding Box Regression
• SVM in RCNN
• Pre-trained Model
• Model Accuracy
• Model Inference Time
• Model Size Comparison
• Transfer Learning
• Object Detection ? Evaluation
• mAP
• IoU
• RCNN ? Speed Bottleneck
• Fast R-CNN
• RoI Pooling
• Fast R-CNN ? Speed Bottleneck
• Faster R-CNN
• Feature Pyramid Network (FPN)
• Regional Proposal Network (RPN)
• Mask R-CNN

Introduction to RNN and GRU

• Issues with Feed Forward Network
• Recurrent Neural Network (RNN)
• Architecture of RNN
• Calculation in RNN
• Backpropagation and Loss calculation
• Applications of RNN
• Vanishing Gradient
• Exploding Gradient
• What is GRU
• Components of GRU
• Update gate
• Reset gate
• Current memory content
• Final memory at current time step

RNN, LSTM

• What is LSTM
• Structure of LSTM
• Forget Gate
• Input Gate
• Output Gate
• LSTM architecture
• Types of Sequence-Based Model
• Sequence Prediction
• Sequence Classification
• Sequence Generation
• Types of LSTM
• Vanilla LSTM
• Stacked LSTM
• CNN LSTM
• Bidirectional LSTM
• How to increase the efficiency of the model
• Backpropagation through time
• Workflow of BPTT

Faster Object Detection Algorithm

• YOLO v3
• YOLO v4
• Darknet
• OpenVINO
• ONNX
• Fast R-CNN
• Faster R-CNN
• Mask R-CNN

BERT Algorithm

• What is BERT
• Brief on types of BERT
• Applications of BERT

Introduction to Large Language Models

• What is a Large Language Model

LLM Architectures

• Encoders and Decoders
• Model Ontology
• Encoders
• Decoders
• Encoders-Decoders
• Architectures at a glance

Prompting and Prompt Engineering

• Affecting the distribution over Vocabulary
• Affecting the distribution over Vocabulary
• Prompting
• Prompt Engineering
• In-context Learning and Few-shot Prompting
• Example Prompts
• Advanced Prompting Strategies

Issues with Prompting

• Prompt Injection
• Memorization

Training

• Training
• Hardware Costs

Decoding

• Decoding
• Greedy Decoding
• Non-Deterministic Decoding
• Temperature

Hallucination

• Hallucination
• Groundedness and Attributability

LLM Applications

• Retrieval Augmented Generation
• Code Models

Multi-Modal

Language Agents

OCI Generative AI Introduction

• OCI Generative AI Service
• How does OCI Generative AI service work
• Pretrained Foundational Models
• Fine-tuning
• Dedicated AI Clusters

Chat Models

• Tokens
• Pretrained Chat Models
• Chat Model Parameters
• Preamble Override
• Temperature
• Chat Model Parameters
• Top k
• Top p
• Frequency and Presence Penalties

Demo Chat Models

Demo OCI Generative AI Service Inference API

Demo Setting up OCI Config for Generative AI API

Embedding Models

• Embeddings
• Word Embeddings

Semantic Similarity

Sentence Embeddings

Embeddings use case

Embedding Models in Generative AI

Embedding Models in Generative AI

Demo Embedding Model

Customize LLMs with your data

• Training LLMs from scratch with my data
• In-context Learning / Few-shot Prompting
• Fine-tuning a pretrained model
• Fine-tuning Benefits
• Retrieval Augmented Generation (RAG)
• Customize LLMs with your data

Fine-tuning and Inference in OCI Generative AI

• Fine-tuning and Inference
• Fine-tuning workflow in OCI Generative AI
• Inference workflow in OCI Generative AI
• Dedicated AI Clusters
• T-Few Fine-tuning

T-Few fine-tuning process

Reducing Inference costs

Inference serving with minimal overhead

Dedicated AI Clusters Sizing and Pricing

• Dedicated AI Cluster Units
• Dedicated AI Cluster Units Sizing
• Dedicated AI Clusters Sizing
• Example Pricing

Demo Dedicated AI Clusters

Generative AI Fine-tuning Configuration

• Fine-tuning Configuration
• Fine-tuning Parameters (T-Few)
• Understanding Fine-tuning Results

Demo Fine-tuning and Custom Models

Demo Inference using Endpoint

OCI Generative AI Security

• Dedicated GPU and RDMA Network
• Model Endpoints
• Customer Data and Model Isolation
• Generative AI leverages OCI Security Services

Retrieval Augmented Generation

• Retrieval Augmented Generation
• RAG Framework
• RAG Techniques
• RAG Pipeline

NNX compatible

Database-Native Vector Embedding Generation

Vector Index

Vector Index Syntax

Similarity Searches in Oracle 23i

Vector Search SQL

Vector Search

AI Vector Search powers Gen AI pipelines

Application Development

Chatbot Introduction

• Chatbot Introduction
• Demo Chatbot

Chatbot Architecture & Basic Components

• Chatbot Architecture
• OCI Generative AI and LangChain Integration
• LangChain Components

Models, Prompts and Chains

• LangChain Prompt, Model and Chain Interaction
• LangChain Prompt Templates
• String Prompt Template and PromptValue
• Chat Prompt Template and PromptValue
• LangChain Models
• LangChain Models ? OCI Chat Models
• LangChain Models ? OCI Embedding Models
• LangChain Chains
• LangChain Chains

Setting Up a Development Environment

Demo Setup Development Environment

Demo Prompts, Chains, and LLMs

Extending Chatbot by Adding Memory

• LangChain Memory
• Memory
• Memory Chat Messages
• LangChain Memory Per User
• Demo Memory
• Demo Streamlitand Memory

Extending Chatbot by Adding RAG

• RAG with LangChain
• Retrieval Augmented Generation (RAG) with LangChain
• Read and Split Documents
• Embed documents and store in the vector database
• Retrieve documents and send as a context to the LLM
• Demo RAG - Indexing
• Demo RAG - Retrieval and Generation

Extending Chatbot by Adding RAG + Memory

• RAG Plus Memory
• Adding chat history as context
• Print of Response
• Demo RAG Plus Memory and Tracing with LangSmith
• Demo Evaluate Model using LangSmith
• Chatbot Technical Architecture

Deploy Chatbot to OCI Compute Instance

• Deploy Chatbot to OCI Compute Instance (Virtual Machine)
• Demo Deploy Chatbot to VM

Deploy Chatbot to OCI Data Science

• Deploy LangChain Application to Data Science as Model

Prompt Engineering Fundamentals

• Generative AI and Large Language Models
• Define Prompt Engineering: Elements of a Prompt
• Parameters of a Prompt
• Prompt Iteration and Evaluation
• Role Prompting
• Quiz: Prompt Engineering Fundamentals

Techniques of Prompting

• Zero-shot Prompting
• Few-shot Prompting
• Chain-of-Thought Prompting
• Quiz: Techniques of Prompting
• Challenge: Techniques of Prompting
• Solution: Techniques of Prompting

Examples of Prompt Engineering for Everyday Success

• Enhancing English Language Skills with Prompt Engineering
• Managing Social Media with Prompt Engineering
• Parenting Aid with Prompt Engineering

Examples of Prompt Engineering for Software Developers

• Learning to Code with Prompt Engineering
• Digital Product Creation with Prompt Engineering
• Web Development with Prompt Engineering
• SaaS Product Development with Prompt Engineering

Getting Started with ChatGPT

• Introduction to ChatGPT
• Message Types and Prompt Parameter Settings in ChatGPT

Making Professional Cover Letters with ChatGPT

• The Basics of Cover Letters
• Writing Cover Letters with ChatGPT
• Cover Letters for Different Experience Levels
• Cover Letters for Different Industries and Job Roles
• Summary: Cover Letters

Building Professional Resumes with ChatGPT

• The Basics of Resumes
• Creating a Resume with ChatGPT
• Updating a Resume with ChatGPT
• Resume Formatting
• Case Studies
• Summary: Resumes

Writing Professional Emails with ChatGPT

• A Simple Email
• Emails for Different Scenarios
• Responding to Emails
• Summary: Emails

Optimize Your Linked In Profile with ChatGPT

• Basics of a LinkedIn Profile
• Optimizing Your Profile
• Creating a Job-Specific Profile
• Summary: LinkedIn Profile

Exploring Job Search Strategies with ChatGPT

• Finding Jobs by Interest and Skills
• Researching Companies and Job Titles
• Preparing for Interviews
• Summary: Job Search Strategies

Introduction to Cloud Computing

• In this module, you will learn what Cloud Computing is and what are the different models of Cloud Computing along with the key differentiators of different models. We will also introduce you to virtual world of AWS along with AWS key vocabulary, services and concepts.
  • A Short history
  • Client Server Computing Concepts
  • Challenges with Distributed Computing
  • Introduction to Cloud Computing
  • Why Cloud Computing
  • Benefits of Cloud Computing

Amazon EC2 and Amazon EBS

• In this module, you will learn about the introduction to compute offering from AWS called EC2. We will cover different instance types and Amazon AMIs. A demo on launching an AWS EC2 instance, connect with an instance and hosting a website on AWS EC2 instance. We will also cover EBS storage Architecture (AWS persistent storage) and the concepts of AMI and snapshots.
  • Amazon EC2
  • EC2 Pricing
  • EC2 Type
  • Installation of Web server and manage like (Apache/ Nginx)
  • Amazon EBS
  • Demo of AMI Creation
  • Backup, Restore
  • Exercise
  • Mock
  • Hands on both Linux and Windows

Amazon Storage Services S3 (Simple Storage Services)

• In this module, you will learn how AWS provides various kinds of scalable storage services. In this module, we will cover different storage services like S3, Glacier, Versioning, and learn how to host a static website on AWS.
  • Versioning
  • Static website
  • Policy
  • Permission
  • Cross region Replication
  • AWS-CLI
  • Mount Point with S3
  • Life cycle
  • Classes of Storage
  • AWS CloudFront
  • Real scenario Practical
  • Hands-on all above

Cloud Watch & SNS

• In this module, you will learn how to monitoring AWS resources and setting up alerts and notifications for AWS resources and AWS usage billing with AWS CloudWatch and SNS.
  • Amazon Cloud Watch
  • SNS - Simple Notification Services
  • SQS
  • Cloud Watch with Agent
  • Cloud Watch with System Manager

Scaling and Load Distribution in AWS

• In this module, you will learn about 'Scaling' and 'Load distribution techniques' in AWS. This module also includes a demo of Load distribution & Scaling your resources horizontally based on time or activity.
  • Amazon Auto Scaling
  • Auto scaling policy with real scenario based
  • Type of Load Balancer
  • Path Based load balancer
  • Hands on with scenario based
  • Routing policy on Load balancer

AWS VPC

• In this module, you will learn introduction to Amazon Virtual Private Cloud. We will cover how you can make public and private subnet with AWS VPC. A demo on creating VPC. We will also cover overview of AWS Route 53.
  • Amazon VPC with subnets
  • Gateways
  • Route Tables
  • Subnet
  • Cross region Peering
  • Endpoint Creation with VPC

Identity and Access Management Techniques (IAM)

• In this module, you will learn how to achieve distribution of access control with AWS using IAM.
  • Amazon IAM
  • add users to groups, manage passwords, log in with IAM-created users.
• User
• Group
• Role
• Policy

Amazon Relational Database Service (RDS)

• In this module, you will learn how to manage relational database service of AWS called RDS.
  • Amazon RDS
  • Type of RDS
  • RDS Failover
  • RDS Subnet
  • RDS Migration
  • Dynamo DB (No SQL DB)
  • Redshift Cluster
  • SQL workbench
  • JDBC / ODBC

Multiple AWS Services and Managing the Resources' Lifecycle

• In this module, you will get an overview of multiple AWS services. We will talk about how do you manage life cycle of AWS resources and follow the DevOps model in AWS. We will also talk about notification and email service of AWS along with Content Distribution Service in this module.
  • Cloud Trail,
  • SQS

AWS Architecture and Design

• In this module, you will cover various architecture and design aspects of AWS. We will also cover the cost planning and optimization techniques along with AWS security best practices, High Availability (HA) and Disaster Recovery (DR) in AWS.
  • AWS Backup and DR Setup
  • AWS High Availability Design
  • AWS Best Practices (Cost +Security)
  • AWS Calculator & Consolidated Billing

Migrating to Cloud & AWS

• In this module, you will learn how to migrate to cloud.
  • Migration to Cloud
  • Migration to AWS
  • Step-by-step process

Router S3 DNS

• Public DNS
• Private DNS
• Routing policy
• Records
• Register DNS
• Work with third-party DNS as well

Cloud Formation

• Stack
• Templet
• JSON / YMAL

Elastic Beanstalk

EFS / NFS (hands-on practice)

Hands-on practice on various Topics

• ECS, EKS (Kubernetes), Docker
  • Comprehensive hands-on with Dockers & Kubernetes Components
  • Docker & Kubernetes Architecture & Components and installation
  • Get introduced to deploy stateful and stateless apps on the cluster
  • Learn how to expose the app outside the cluster and to auto-scale apps
  • Expertise in learning with use cases of Containers and Docker
• Linux
  • Installation of Linux
  • Configuration
  • Manage
  • Installation of app on Linux (apache / Nginx etc)
  • AWS cli configuration on Linux
  • Complete hands-on on Linux.
• Python
• Boto
• DMS
• System Manager
• Mock
• Interview preparation
• Scenario-based lab and practical
• Each topic and service will be covered with lab and theory.
• Security: KMS / SSM/ WAF
• Storage: EFS, NFS, FSX, Storage Gateway

Manage Azure identities and governance (15-20%)

• Manage Azure AD objects
  • create users and groups
  • manage user and group properties
  • manage device settings
  • perform bulk user updates
  • manage guest accounts
  • configure Azure AD Join
  • configure self-service password reset
  • NOTE: Azure AD Connect; PIM
• Manage role-based access control (RBAC)
  • create a custom role
  • provide access to Azure resources by assigning roles
  • subscriptions
  • resource groups
  • resources (VM, disk, etc.)
  • interpret access assignments
  • manage multiple directories
• Manage subscriptions and governance
  • configure Azure policies
  • configure resource locks
  • apply tags
  • create and manage resource groups
  • move resources
  • remove RGs
  • manage subscriptions
  • configure Cost Management
  • configure management groups

Implement and Manage Storage (10-15%)

• Manage storage accounts
  • configure network access to storage accounts
  • create and configure storage accounts
  • generate shared access signature
  • manage access keys
  • implement Azure storage replication
  • configure Azure AD Authentication for a storage account
• Manage data in Azure Storage
  • export from Azure job
  • import into Azure job
  • install and use Azure Storage Explorer
  • copy data by using AZ Copy
• Configure Azure files and Azure blob storage
  • create an Azure file share
  • create and configure Azure File Sync service
  • configure Azure blob storage
  • configure storage tiers for Azure blobs

Deploy and Manage Azure Compute Resources (25-30%)

• Configure VMs for high availability and scalability
  • configure high availability
  • deploy and configure scale sets
• Automate deployment and configuration of VMs
  • modify Azure Resource Manager (ARM) template
  • configure VHD template
  • deploy from template
  • save a deployment as an ARM template
  • automate configuration management by using custom script extensions
• Create and configure VMs
  • configure Azure Disk Encryption
  • move VMs from one resource group to another
  • manage VM sizes
  • add data discs
  • configure networking
  • redeploy VMs
• Create and configure containers
  • create and configure Azure Kubernetes Service (AKS)
  • create and configure Azure Container Instances (ACI)
  • NOT: selecting a container solution architecture or product; container registry settings
• Create and configure Web Apps
  • create and configure App Service
  • create and configure App Service Plans
  • NOT: Azure Functions; Logic Apps; Event Grid

Configure and Manage Virtual Networking (30-35%)

• Implement and manage virtual networking
  • create and configure VNET peering
  • configure private and public IP addresses, network routes, network interface, subnets, and virtual network
• Configure name resolution
  • configure Azure DNS
  • configure custom DNS settings
  • configure a private or public DNS zone
• Secure access to virtual networks
  • create security rules
  • associate an NSG to a subnet or network interface
  • evaluate effective security rules
  • deploy and configure Azure Firewall
  • deploy and configure Azure Bastion Service
  • NOT: Implement Application Security Groups; DDoS
• Configure load balancing
  • configure Application Gateway
  • configure an internal load balancer
  • configure load balancing rules
  • configure a public load balancer
  • troubleshoot load balancing
  • NOT: Traffic Manager and Front Door and Private Link
• Monitor and troubleshoot virtual networking
  • monitor on-premises connectivity
  • use Network Performance Monitor
  • use Network Watcher
  • troubleshoot external networking
  • troubleshoot virtual network connectivity
• Integrate an on-premises network with an Azure virtual network
  • create and configure Azure VPN Gateway
  • create and configure VPNs
  • configure ExpressRoute
  • configure Azure Virtual WAN

Monitor and Back up Azure Resources (10-15%)

• Monitor resources by using Azure Monitor
  • configure and interpret metrics
  • analyze metrics across subscriptions
  • configure Log Analytics
  • implement a Log Analytics workspace
  • configure diagnostic settings
  • query and analyze logs
  • create a query
  • save a query to the dashboard
  • interpret graphs
  • set up alerts and actions
  • create and test alerts
  • create action groups
  • view alerts in Azure Monitor
  • analyze alerts across subscriptions
  • configure Application Insights
  • NOT: Network monitoring
• Implement backup and recovery
  • configure and review backup reports
  • perform backup and restore operations by using Azure Backup Service
  • create a Recovery Services Vault
  • use soft deletes to recover Azure VMs
  • create and configure backup policy
  • perform site-to-site recovery by using Azure Site Recovery
  • NOT: SQL or HANA