Master Data Science with AI, Machine Learning & Big Data

• What is Data Science and Data Analytics?
• Computer System and Computer Components
• Binary Language and ASCII Code
• Memory Units and Number Systems
• Various Terminology about Data science
• Computer - Operating System
• Microsoft office

• Excel Fundamentals
• Advanced Excel Formulas & Functions
• Excel For Data Analytics
• Data Visualization with Excel
• Excel Power Tools
• Data Formatting
• Excel Pivot Table & Pivot Chart
• Data Operation with Advanced Excel
• Excel New Feature

• Managing Worksheets
• Create MIS Reports in Excel
• MIS Report Elements
• Managing Dashboard
• Presenting a data summary
• Fundamental Data Analysis
• Data Visualization with Analytics
• Information Measure in Excel

• MySQL Functions
• MySQL - Import and Export data
• Organizes Data Structure into Data Tables Services
• Manage & Manipulate Database
• Database operations -create/manage/ access & search
• Updates, join, clause
• Retrieve Data information

• Introduction to SQL SERVER
• Storing and Retrieving Databases
• Sql Optimization and CRUD operations
• Data Import and Export from different sources
• SQL Operators, Join, Clause
• Deep Dive into SQL Functions
• Working with Subqueries, Views and Stored Procedure

• Power Bi Desktop & Power Bi Query Editor
• Connecting & Monitoring Various Data Sources
• Data Storage, And Then Transforming Data
• Bi Tools for Aggregating, Analyzing, Visualizing & Sharing Data.
• Creating Reports & Dashboards
• Create Rich, Impact ful, Interactive Visualization
• Centralize Your Data in A Trusted and Secure Hub
• Deepen Data Insights with Ai-Driven Analytics
• Publish & Share Reports with Power Bi Pro

• Create Interactive Business Intelligence Dashboards
• Connect, Visualize, and Share Data
• Create & Distribute an Interactive & Shareable Dashboard
• Transform raw data into interactive dashboards & visualizations
• Well-designed graphics & properties
• Real-time data analysis
• Query translation into visualization
• Data Blending & Data Collaboration

• Notation for writing computer programs
• Types of computer languages
• Cutting-edge coding skills.
• Ways of generating machine code,
• Set of instructions to generate logics
• machine-dependent (0s and 1s) programming language
• compiler or interpreter to translate the program into machine language
• Using a programming editor like IDE & VS etc.

• Object-Oriented Languages Importance
• Class, Objects & Library Files in C++
• Constructor & Destructor Concepts
• Inheritance Concepts
• Polymorphism Concepts
• Abstraction Concepts
• Encapsulation Concepts
• Data Binding & Integrations Concepts
• Input-Output Operations
• File Handling Concepts

• Python Fundamentals
• Python Data Types & Resources
• Library Reference for Python's Many Standard Libraries
• Language Reference for Python's Syntax.
• Set Python Virtual Environment Setup
• Input Output Operations
• Functions & Modules in Python
• Exceptions Handling

• Advanced Oops Concepts in Python with Various Data types
• Working with Set, List, Dict. , Tuple Data, Interfaces in Python
• Packages & Library with Pip
• Python Database Connectivity Configurations
• Data Management & Manipulations (Storage, Fetch, Retrieve, Maintain)
• Implementation Of All Concept In Project Preparations

• Powerful Graphical User Interface Toolkit for Python
• Drag-and-Drop GUI builder, with built-in hosting for Our Apps.
• Tk GUI toolkit shipped with Python.
• Specific Geometry Management methods
• Apply event triggers to the widgets.
• Create Admin. & User Panel to Respond to user interactions.
• PDBC - Python Database Connection Configuration with SQL.

• Linear Algebra Concepts.
• Matrix Operations Like Addition, Subtraction, Multiplication & Inversion
• Linear Models To Solve Real-world Problems
• Linear Regression to predict prices based on historical data.
• Linear Algebra For Data Science & Understand How To Implement It With Python.

• NumPy - Numerical Python Techniques .
• Single & Multi-Dimensional Arrays in NumPy
• NumPy Vectorization, Matrices, Indexing, and Slicing Concepts
• NumPy Mathematical, Arithmetic, Statistics Functions
• Random number generators in NumPy
• Linear Algebra & array computing
• Computing diff. Attributes of NumPy arrays.

• Use open source data analysis and manipulation tools
• Cleaning and Plotting data
• Working with data sets with Easy handling of missing data
• Flexible Merging, Joining, Reshaping and Pivoting of data sets
• Functions for analyzing, cleaning, exploring, and manipulating data.
• Powerful data structures for data analysis
• Time Series and Delta Attributes
• Slicing, Indexing & Sub- Setting of large data sets
• Time series-specific functionality
• Date Range Generation
• Frequency conversion
• Pandas Data Frame

• Introduction of Graphical Representation of Information
• Understand Visual Elements Like Charts, Graphs, And Maps,
• Discuss Data visualization Tools in Python
• Understand Trends, Outliers, and Patterns In Data.
• Quickly Identify Patterns, Trends & Correlations Within Data.

• Library For Creating Static, Animated & Interactive Visualizations
• Understand Trends, And Patterns, And To Make Correlations.
• Create Plot By Connecting The Points Defined By X & Y Values.
• Create Publication Quality Plots.
• Matplotlib Utilities Under The “pyplot” Submodule
• Interactive Format Environments Across Platforms
• Customize Visual Style And Layout.
• Creating static, animated, and interactive visualizations.
• Generate A Wide Range Of Plots, Including Line Plots, Scatter Plots, Bar
• Plots, Histograms, Pie Charts, And More.

• Functions For Optimization, Stats And Signal Processing.
• Algorithms For Optimization, Integration, Interpolation Queries
• Algebraic Equations, Differential Equations, Statistics
• Extends Numpy Providing Additional Tools
• Array Computing And Provides Specialized Data Structures
• Numerical Integration
• Image Manipulation & Optimization
• Signal Processing & Fast Transforms

• Including Object Detection, Face Recognition, And Tracking
• Computer vision, machine learning, and image processing
• Process images and videos to identify objects, faces of a human.
• GUI Features in OpenCV
• Techniques to work with videos like object tracking & Camera Calibration
• Object Detection (obj-detect module) techniques like face detection
• OpenCV Python binding.

• Fundamentals of Machine Learning Using Python’s Powerful Libraries
• Describe the various types of Machine Learning algorithms and when to
• use them
• Understand and identify patterns, make predictions, and make decisions
• based on data.
• Explore advanced data science challenges through sample data sets
• Examine machine learning results and recognize under-fitting or
• over-fitting data.

Module 21. TENSORFLOW - LIBRARY FOR MACHINE LEARNING & ARTIFICIAL INTELLIGENCE

• Multiple APIs (Application Programming Interfaces)
• Create Deep Learning Models
• Using Wrapper Libraries To Process TensorFlow Nodes
• Named Abstract Computation Input & Output Attributes
• Tasks Focus On Training And Inference Of Deep Neural Networks
• Create Machine Learning Models For Desktop, Mobile, Web & Cloud
• AI Model - Uses The Flatten, Dense, And Dropout Layers
• Tensor Edges Graph Representing Multi-dimensional Data Arrays
• Linear Regression With TensorFlow

Module 22. GITHUB - CLOUD-BASED SERVICES

• Cloud-based service for software development and version control using Git
• Allows developers to store and manage their code
• Storing, tracking, and collaborating on open-source projects

Module 23. INDUSTRY STANDARD PROJECTS

• Data Scrubbing/Cleaning
• Exploratory Data Analysis
• Interactive Data Visualization
• Cluster the Information in a Given Dataset
• Data Models To Wave Artificial Intelligence And Machine Learning

Module 24. SKILLS TO MASTER FOR INTERVIEW PREPARATIONS

• Share the job description
• Practice mock interviews
• Analyze your performance
• Organize your documents - digital copy of CV, update your social media profile, showcase student's accomplishments
• Preparation & Tips for a phone interview & video interview
• Interview rounds Preparations: HR Interview, Technical Interview, Managerial Interview