
DATA SCIENTIST MASTER PROGRAMME
What you'll learn
- Master Python for Data Analysis Learn Python from scratch and use libraries like Pandas, NumPy, and Matplotlib for data manipulation and visualization.
- Dive Deep into Data Science & Machine Learning Understand statistics, EDA, and build ML models using scikit-learn for regression, classification, and clustering.
- Work with Databases using SQL Query, filter, and manage data efficiently using MySQL or PostgreSQL — a must-have for any data professional.
- Analyze Data with Excel & Power BI Use Advanced Excel functions and Power BI for dashboard creation, data cleaning, and interactive reporting.
- Visualize Insights with Tableau Design stunning dashboards and visual stories using Tableau, turning raw data into clear insights.
Learning Objectives
- PYTHON
- PYTHON LIBRARIES
- DATA SCIENCE
- MACHINE LEARNING
- ADVANCED EXCEL
- SQL
- POWER BI
- TABLEAU
Course content
- 7 Modules
- 90 Sessions
- 5 Months Duration
PYTHON INTRODUCTION
- Installation and Setting up path
Features - Python variables
- Input & Output and Import
- Why Learn Python
- Who used Python
PYTHON BASICS
Using Pycharm & Scripting Keywords & Identifiers Operators, Indentations
DATA TYPES
Basic Data types: int, float, string, Boolean and Complex Numbers and String Tuple and List Dictionary and Set Arrays
BUILT IN FUNCTIONS
String, String slices Date Math Random and Statistics PDF Data Extraction CVS module
TUPLES
Introduction to Tuples Working with Tuples Tuple Operations Function and Methods
LISTS
Introduction to Lists Working with lists Lists Operations Function and Methods
SETS
Introduction to Sets Working with Sets Sets Operations Function and Methods
FLOW CONTROLS
If…else Elif For, for else, while Break and Continue Pass Looping Techniques
FUNCTIONS
Types of Functions Function Arguments Recursion Anonymous Function Global, local and Nonlocal Lambda Functions Modules Packages
FILE HANDLING
Reading & Writing Files Manipulating File Pointer Type of Files File Operations Directories File I/O Attributes, File Methods
EXCEPTION HANDLING
Try, Except and Finally Try else Custom Exception Error Vs. Exception
OOPS CONCEPTS
Real-time in OOPS Access Specifiers Class and Objects Methods Overloading and Overriding Inheritance Abstraction and Data Hiding Properties &Self-keyword
OS AND SYSTEM SERVICES
OS module Environment variables, Paths, directories, and filenames. Working with file systems, Dates and times
MULTITHREADING
Starting a New Thread Creating Thread Using Threading Module Synchronizing Threads Multithreaded Priority Queue
REGULAR EXPRESSION
pattern matching and searching Real time parsing of networking or system data using regex validation Concepts
REALTIME HACKS
Web Scraping Chabot & Language Translate Find the Similarity ratio between text Tagging Sentence to find key word Google map integration Bubble sort algorithm QR code generator Spell checker Scraping Wikipedia Anagram & Screenshot app,Python for networking Getting input from user Working with images & building a photo gallery
NUMPY
Numpy Introduction, Numpy Arrays, Data Types in Numpy, Array Indexing, Array Slicing, Array Shape, Array Reshape, Array Iteration, Array Join, Array Split, Array Search & Sorting, Array Filter
PANDAS
Introduction Pandas, Series Pandas, Data Frames, Pandas Read CSV & JSON, Pandas Analyzing Data, Data Cleaning
PANDAS ANALYZING DATA
MATPLOT
Introduction, Pyplot Plotting, Markers, Line Labels, Grid, Subplot, Scatter Plot, Bar Chart, Histogram, Pie Chart
DATA SCINECE INTRODUCTION
STATISTICS
STATISTICS
STATISTICS
STATISTICS
STATISTICS
STATISTICS
MACHINE LEARNING
MACHINE LEARNING STATISTICS & DATA DISTRIBUTION
SUPERVISED LEARNING MODEL
UNSUPERVISED LEARNING MODEL
ADVANCED EXCEL INTRODUCTION
FORMULAS & FUNCTIONS, Aggregate Function, Logical Function, Lookup & References, Financial Functions, Formatting and Proofing
CONDITIONAL FORMATTING
Conditional Formatting using New Rule Conditional Formatting using Formula
PIVOT TABLES
Creating Simple Pivot Tables, Classic Pivot table Basic and Advanced Value Field Setting, Calculated Field & Calculated Items, Grouping based on numbers and Dates
POWER PIVOT
Activating Power pivot Usage of Data model DAX Calculation Relational Data
SLICERS AND CHARTS
Using SLICERS, Filter data with Slicers Various Charts i.e. Bar Charts/Pie Charts/Line Charts Manage Primary and Secondary Axis
DATA AND VALIDATION
Number, Date & Time Validation Text and List Validation Custom Validation Dropdown List Validation.
ANALYZING AND ORGANIZING DATA
Creating Scenarios, Working with Data Tables, Using Goal Seek, Using Solver, Using Consolidating Data by Position or Category, Consolidating Data Using Formulas Excel
VBA MS ACCESS
Macro Builder, Create a standalone macro, Create an embedded macro, Add actions to a macro, Control program flow with If, Else If, and Else, Create sub macros, Group related actions together, Expand and collapse macro actions or blocks, Copy and paste macro actions, Share a macro with others
SQL INTRODUCTION
Get started with database, SQL and MySQL What is database? Why use SQL? Importance of MySQL
BASICS OF SQL
First Steps in SQL, Creating a database, Introduction to data types, Creating a table
INSTALLING SQL
Get acquainted with the interface
SQL SERVER LANGUAGES AND RELATIONAL DATABASES
DDL DCL DML TCL
RELATIONAL DATABASE TERMINOLOGY
Relational Database essentials, Primary key, Foreign key, Unique key and null values
THE SELECT STATEMENT
Load the database, Loading employees’ database, Starting with SELECT statement, Select-From Where And-Or (In-not in) Like-not like, Wildcard characters Between-and Is not null-is null, Select distinct, Aggregate statement, Order by-Group by Using Aliases, Having and Limit
SQL STATEMENT
Insert statement, Inserting data INTO table, Update statement, Commit and rollback, Delete statement, Drop vs Truncate, AGGREGATE FUNCTIONS, Functions Count Sum Min() and Max Avg Round()
POWER BI INTRODUCTION
What is Power BI, Why we have to use?
ARCHITECTURE
Components
SUPPORTED DATA SOURCES
Data Sources : Excel, SQL, CSV, JSON, Access
COMPARISON WITH OTHER BI TOOLS
Power BI vs Tableau
DATA MODELLING
Using Data Modeling and Navigation, Creating Calculated, Columns, Creating Calculated Tables, Managing Time-Based Data
DASHBOARD OPTIONS
Exploring Different Datasets, Creating and Sharing Dashboards, Tiles in Dashboard, Data Gateway
VISUALIZATION OPTIONS
Creating Simple Visualizations, Creating Map Visualizations, Using Combination Charts, Using Tables, Modify Colors in Charts, Adding Shapes, Images and Text box, Styling Reports, Duplicating Reports
EXCEL INTEGRATION
Using Excel Data Importing xlsx Files
DASHBOARDS
Using Power BI Desktop for Report Sharing, Printing Power BI Dashboards, Export Options, Publishing Report to Web, Using & Editing Content Pack
DAX BASICS IN POWER BI
DAX Architecture, Entity Sets DAX Data Types, Syntax Rules DAX Measures and Calculation Data Modeling Options in DAX
ADMINISTRATION ROLE
Purchasing REST API Security
TABLEAU INTRODUCTION
BI Concepts What is TABLEAU? Why Data Visualization? Unique Features compared to Traditional BI Tools TABLEAU Overview & Architecture File Types & Extensions
DATA CONNECTIONS IN TABLEAU INTERFACE
Data Connections in the Tableau Interface, Connecting to Tableau, Data Server, Types of Join, When to Use Joining, What is Data Blending, When to Use Data Blending, Joining vs. Blending, Creating Data Extracts in Tableau, Shadow Extracts, Prepare your Data for Analysis
ORGANIZING AND SIMPLIFYING DATA
Filters. Applying Filters Quick Filters Sorting of Data Creating Combined Fields Creating Groups and Defining Aliases Working with Sets and Combined Sets Drill to Other Levels in a Hierarchy Grand totals and Subtotals Tableau Bins Fixed Sized Bins Variable Sized Bins Creating and using Parameters Exploring Parameter Controls Using parameters for titles, field selections, logic statements, Top X Cross Tabs [Pivot Tables] Page Trials Total and Sub-Total
BUILDING CHART TYPES
Working with Combined Axis Working with Combination Charts Working with Geocoding and Geographic Mapping Using Scatter Plots Using Text tables and Highlight tables Using Heat Maps Using Histograms Using Pie Charts Using Bullet Charts
ADVANCED CHART TYPES
Using Pareto Charts Using Waterfall Charts Using Gantt Charts Using Box Plots Using Sparkline Charts Using Density Charts Using KPI Charts Small Multiples Working with aggregate versus disaggregate data What is Market Basket Analysis Performing Market Basket Analysis
LOGIC STATEMENTS
Formatting Options in Formatting Visualizations Working with Labels and Annotations Effective Use of Titles and Captions Introduction to Visual Best Practices
MAPPING
Importing and Modifying Custom Geocoding Working with Symbol Map and Filled Map Using Background Image Exploring Geographic Search Perform Pan Zoom Lasso and Radial Selection Working with WMS Server Maps [Web Map Service]
STATISTICS
Add Reference Lines Bands and Distribution Adding Reference Lines Adding Reference Bands Adding Reference Distribution Working Reference Lines Bands and Forecasting Trend lines and Trend Models
DASHBOARD
Build Interactive Dashboards Best practices for creating effective dashboards Creating a Dashboard and Importing Sheets Interaction Exploring Dashboard Actions Use of Running Actions & Dashboard Actions How to Share your Reports & Exporting your Work
Description
Become a Skilled Data Analyst with Industry-Leading Tools. This program provides comprehensive training in data analytics, from fundamentals to advanced techniques. Learn to work with data visualization, statistical analysis, and machine learning using industry-standard tools. Gain hands-on experience in handling real-world data, uncovering insights, and making data-driven decisions. Enhance your expertise and improve your career prospects in the growing field of data analytics.
Mapped Certificate

Google Flutter Certification
via Google Developer's Certification Program

MongoDB University
For Flutter + Firebase integration
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Lectures
7 Modules with Certificates
Duration
5 Months
Language
English, Tamil
Mode
Online, Offline
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