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Become proficient in the Top 10 Data Science technologies. Master fundamental concepts and key techniques to shape a robust and rewarding professional future.

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₹9999 ₹1999/-

Master in Data Science Skills

Grow 10X Bundle

Become proficient in the Top 10 Data Science technologies. Master fundamental concepts and key techniques to shape a robust and rewarding professional future.

Enroll Now & Get Flat 80% OFF!

₹9999 ₹1999/-

Master in Data Science Skills

Grow 10X Bundle

Become proficient in the Top 10 Data Science technologies. Master fundamental concepts and key techniques to shape a robust and rewarding professional future.

Enroll Now & Get Flat 80% OFF!

₹9999 ₹1999/-

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Why Data Science is the Key to a Prosperous Career?

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A foundational understanding of Web-development Ecosystem 

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Learn how to develop fast, responsive & interactive websites

Use of trending technologies like - Flask, Redis & Machine Learning. 

Effectively implement machine learning concepts in web development.

How to write functional yet seamless JavaScript Code.

Build fully working web applications using simple steps.

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Upskill and Invest in a Glowing Data Science Career

Master and gain 10 certifications @ ₹1999 only

Transform into an advanced data science professional from a beginner. Learn from a curated selection of self-paced, upskilling courses with detailed modules offering expert guidance.

Python Zero to Hero
Introduction to Data Science with R
R Programming
Data analytics using pandas
Computational Thinking
Machine Learning
Data Visualisation in Python
Computational Thinking
Modern HTML & CSS
Machine Learning
Redis & Python RESTful API

Upskill and Invest in a Glowing Data Science Career

Master and gain 10 certifications @ ₹1999 only

Transform into an advanced data science professional from a beginner. Learn from a curated selection of self-paced, upskilling courses with detailed modules offering expert guidance.

Python Zero to Hero
Introduction to Data Science...
R Programming
Computational Thinking
Data Visualisation...
Machine Learning
Data analytics using pandas

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  • Certificates are issued by an edtech company GUVI.
  • Certificates are globally recognized & they upgrade your programming profile.
  • Certificates are generated after the completion of course.
  • Certificates are sharable on your LinkedIn profile
  • Certificates are issued by an edtech company GUVI.
  • Certificates are globally recognized & they upgrade your programming profile.
  • Certificates are generated after the completion of course.
  • Certificates are sharable on your LinkedIn profile

From Fundamentals to Expertise

After this Course, You’ll be Able to

Master Python for effective implementation in Data Science projects.

Apply statistical programming for practical implementation in Data Science tasks.

Integrate Data Science insights seamlessly with advanced PowerBI visualisation skills.

Cultivate computational thinking for adept problem-solving in real-world scenarios.

Harness MongoDB expertise for efficient NoSQL database management in Data Science.

Acquire proficiency in machine learning to build and train diverse models.

Achieve Your Career Goals with This Course

Learn from scratch, make a career switch, or simply upgrade your skills, this course is everything you need if you’re a 

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Complete individual courses and gain certifications

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Why Choose GUVI?

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"You will be lucky to find quality courses on GUVI. I must say that I was really lucky to get courses at such a low and discounted price. I got more than 9 hours of video and around 20 more resources to gain knowledge of programming. GUVI provides a wide variety of courses both technical and non-technical. I suggest GUVI is the best choice."

"What makes GUVI different is that it provides vernacular courses which make it easy to understand & practice platforms like CodeKata & WebKata, all these helped me improve my practical programming skills in the front end, back end. I highly recommend it if you want to get started with something new."

"I have opted for a combo-course that starts with the basics of the popular technologies and made me a pro in its domain... Codekata is very damn helpful to crack placements because it improved my efficiency in coding... we just need to be persistent and that’s all it takes. I am very happy to encounter GUVI!"

What Our Learners say about Us?

"You will be lucky to find quality courses on GUVI. I must say that I was really lucky to get courses at such a low and discounted price. I got more than 9 hours of video and around 20 more resources to gain knowledge of programming. GUVI provides a wide variety of courses both technical and non-technical. I suggest GUVI is the best choice."

"What makes GUVI different is that it provides vernacular courses which make it easy to understand & practice platforms like CodeKata & WebKata, all these helped me improve my practical programming skills in the front end, back end. I highly recommend it if you want to get started with something new."

"I have opted for a combo-course that starts with the basics of the popular technologies and made me a pro in its domain... Codekata is very damn helpful to crack placements because it improved my efficiency in coding... we just need to be persistent and that’s all it takes. I am very happy to encounter GUVI!"

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Frequently Asked Questions

What is the refund policy?

Customer satisfaction is our first priority. If you are not satisfied with the course, send a mail to [email protected] with the reason for refund and your feedback on the course, within 7 days of purchasing the course. Your refund will be processed immediately. 

Apart from these courses, will I get access to any practice platforms?

You will gain full access to CodeKata - a gamified practice platform which hosts 1000+ curated coding problems, Webkata - a gamified practice platform for Web problems, Debugging - A practise Platform to practise debugging problems and IDE - an Integrated Development Environment that lets you write, edit, run, test & debug your code. 

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When can I start learning? Or what is the duration of this course?

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Master Data Science Skills

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Python Zero to Hero
Syllabus:
Beginner Module
  • Introduction to Python & Features of Python
  • PVM, Frozen Binaries & Memory managemen
  • Execution & Viewing the Byte Code
  • Installing & Testing Python for Windows
  • Setting the Path & Executing First Python Program
  • Comments in Python & Docstrings
  • Datatypes & Built-in datatypes
  • Bool Datatype, Sequences in Python & Sets
  • Literals in Python & Determining the Datatype of a Variable
  • Variables Rules & Conventions
  • User-defined Datatypes & Constants
  • Operators
  • Control Statements
  • The if Statement
  • A Word on Indentation &
  • The if … elif … else Statement
  • The while Loop
  • The for Loop, The else Suite, The break Statement, The continue Statement
  • Infinite & Nested Loops, The pass, and The assert statement
  • Defining & Calling a Function
  • Returning Results, Multiple values from a Function & Pass by object reference
  • Formal, Actual & Positional Arguments
  • Keyword & Default Arguments
  • Variable Length Arguments & Recursive function
Intermediate Module
  • Anonymous Functions or Lambdas
  • Generators & Decorators
  • Structured Programming & modules
  • Input, Filter and Map
  • Strings - Creating & Length of a String
  • Indexing in Strings
  • Slicing & Reverse Strings
  • Case Modification
  • Membership, Replacement & Sub Strings
  • Split, Join, Find, Index
  • Concatenation of Strings
  • Lists- Create
  • Lists - Slicing and Updating
  • Lists - Add and Remove Items
  • List Remaining Methods
  • Membership & Nested Lists
  • List Comprehensions
  • Tuples Creating and Modifications
  • Basic Operations on Tuples
  • Sets
  • Operations on Dictionaries
  • Dictionary Methods
  • Using for loops, Sorting Elements of Dictionary using Lambdas
Advanced Module
  • OOPS Concepts & Features
  • Constructor, Variables & Namespace
  • Method types, Passing member & Inner Classes
  • Constructors in Inheritance
  • Overriding Constructors, Inheritance, Super()
    MRO, Polymorphism,
  • Overloading, Overriding, Duck Typing
  • Errors and Exception, Handling, etc
Expert Module
  • Files in Python, Pickle and With Statement
  • Random Accessing & Zipping
  • Regular Expressions
  • Quantifiers in Regular Expressions
  • Special Characters & Sequences
  • Single Threading, Uses of Thread & Concurrent Programming
  • Thread Class Methods & Multitasking using Multiple Threads
  • Thread Synchronization(Lock and Semaphore)
  • Deadlocks and Avoiding Deadlock
  • Thread Communications using wait() & notify() and Daemon Threads
Introduction to Data Science with R Syllabus:
Beginner Module
  • Basics of Data science
  • Introduction to Big data
  • Application of Big data Analytics
  • Introduction to R
  • In-Built functions in R
  • Basics of Statistics
  • Hypothesis testing
  • Statistical tests
  • Some more inbuilt functions in R
  • Statistical operations in R
  • Plotting in R
  • Basics of Machine learning
  • simple linear regression theory
  • Simple linear regression in R
  • Multiple linear regression theory
  • Multiple linear regression in R
Intermediate Module
  • Logistic regression
  • Metrics in logistic regression
  • Logistic regression model in R
  • Logistic regression metrics in R
  • Decision tree
  • CHAID
  • Random Forest
  • Random forest in R
  • Introduction to Clustering
  • Introduction to K-Means clustering
  • K-Means in R
R programming Syllabus:
Beginner Module
  • R - An Introduction
  • Variables and Operators
  • Vectors
  • Matrices
  • Lists
  • Data Frames
  • Factors and Datasets
  • Summarise functions
  • Conclusion
Intermediate Module
  • Relational Operations
  • Logical Operations
  • Control Statements
  • Looping Statements and Functions
  • Mathematical and Statistical Relational Functions
  • Apply functions
  • Map functions
Advanced Module
  • Dplyr Select
  • Dplyr - Slice, Mutate, Arrange
  • data.table - Select, Filter and Sort
  • Joins
  • Grammar of Graphics
  • Plots and Histograms
  • Pie Charts
  • ggplots
  • Project Task
  • Project Task Solution
Microsoft Power BI Syllabus:
Beginner Module
  • Lab 1 - Learn Power BI step by step(for beginners).
  • Lab 2: - Connecting SQL Server with Power BI.
  • Lab 3: - Line, Area, Stacked, Gauge, KPI and Funnel Graph in Power BI.
  • Lab 4: - Star Schema & Snow Flake design in Power BI project.
Intermediate Module
  • Lab 5: - DAX - Data Analysis Expression - Part 1
Computational thinking Syllabus:
Beginner Module
  • Programming where to start
  • Algorithm Tracing Technique
  • Documentation & Debugging
  • Bitwise & Boolean Algebra
  • Memory Technologies
  • Stack and Heap
  • Compiler vs Interpreter
Intermediate Module
  • Loops and Conditions
  • Nested Loop
  • Strings
  • Array
  • Recursion
Advanced Module
  • Database Management System ( DBMS )
  • SQL
  • JSON
  • API
  • Searching
Expert Module
  • Data Structures and Algorithm
  • Abstract Data Type
  • Big O Notation
  • Data Structures -Stack,Queues
  • Array,Linked List,DLL
  • Hashing
  • Trees
  • Graphs
Tableau - Introduction to Beginners Syllabus:
Beginner Module
  • Introduction to Tableau
  • Why Tableau?
  • Tableau Products & Installation
  • Connecting to Data and different Chart types
  • Data Types
  • Understanding Marks Card
  • When to Use Line Charts
  • Filtering & Groups
  • Dates as Hierarchical Dimensions
Intermediate Module
  • Trend Lines
  • Box Plots
  • Views using Sample Superstore Data - Part 1
  • Views using Sample Superstore Data - Part 2
  • Views using Sample Superstore Data - Part 3
  • Views using Sample Superstore Data - Part 4
  • Customizing & Sharing New Data in Tableau
  • Tableau Calculation Types
  • How to Write Calculations - Part 1
  • How to Write Calculations - Part 2
  • Tooltips
  • Doughnut Chart

Advanced Module
  • Date Hierarchies
  • Converting Discrete & Continuous Dates
  • Parameters - Part 1
  • Parameters - Part 2
  • Parameters - Part 3
  • Parameters - Part 4
  • Level of Detail (LoD) - Part 1
  • Level of Detail (LoD) - Part 2
  • Level of Detail (LoD) - Part 3
  • Introduction to Mapping
  • Working with Geographic Data
  • Shapes, Colors & Sizes
Expert Module
  • Custom Mapping Techniques
  • Custom Geocoding
  • Dual Layer Mapping
  • Dashboard Design Principles - Part 1
  • Dashboard Design Principles - Part 2
  • Important Considerations for Creating Dashboards
  • The Art of Storytelling
  • Storytelling & Neuroscience
  • Emotions & Storytelling
  • Setting Up the Story - Part 1
  • Setting Up the Story - Part 2
  • Setting Up the Story - Part 3
  • Building a Dashboard & an Interactive Story
  • Capstone Project
MongoDB Syllabus:
Beginner Module

Introduction to MongoDB
Setting Environment Variables
Start the mongo Shell
Creating Collections
Final Quiz

Intermediate Module

Creating and Dropping Documents
Query Document 
Query Document AND OR C
MongoDB Update Document
Final Quiz

Advanced Module

Delete Document
MongoDB Projection
Sort,Skip and Limit
Final Quiz

Expert Module

Indexing
MongoDB Aggregation
MongoDB Backup and Restore data
Final Quiz

Data Visualization in Python Syllabus:
Beginner Module
  • Introduction to Data Visualization
  • Matplotlib for Data Visualization
  • Using Matplotlib to draw plots
  • Visualizing & Customizing Plot appearances using Matplotlib
  • Multiple Line PLots
  • Basics of Time serious
  • Time Series Plotting and adding styles to the plots
  • Slicing and Customizing Time Series Data
  • Twin Axes Plotting
  • Bar Plot and Box Plots
  • Violin, Histogram and Scatter
  • Contour Plot and Annotations in Matplotlib
  • Advance Annotations
  • Image Tutorial in matplotlib
Intermediate Module
  • Introduction to Seaborn Library
  • Relational Plots and Subplots in Seaborn
  • Subplotting in Rows and Columns using Relational Plot
  • Line Plots in Seaborn
  • Bar Plots, Box Plots and Point Plots in Seaborn
  • Colour Palettes in Seaborn
Advanced Module
  • Introduction to BOKEH
  • Patch Plots and Scatter Marks in Bokeh
  • Area Plots and Circle Glyphs in Bokeh
  • Rectangle, Oval and Polygon Glyphs in Bokeh
  • Wedges, Arcs and Specialized curves in Bokeh
  • Setting Plot ranges and Axes in Bokeh Plots
  • Twin Axes, Datetime axes and Annotations in Bokeh Plots
  • Categorical and Log Axes in Bokeh
  • Row and Column Layouts in Bokeh Plots
  • Customizing Tools and Legends in Bokeh Plots
  • Column Data Source and Adding Widgets to Bokeh Plots
Data Analysis using Pandas Syllabus:
Beginner Module
  • Introduction
  • Setting up Pandas Environment
  • An Introduction to Jupyter Notebook
  • Loading Data into Pandas
  • A Deeper Look Into Data
  • DataFrames - Basic Functions
  • Dataframes- rows and columns
Intermediate Module
  • Sorting DataFrames
  • Handling Datetime Fields in Pandas
  • Statistical Functions in Pandas
Advanced Module
  • Pandas - Indexes
  • Data Grouped Representation
  • Data Visualization
  • Adding New Data - Merge, Join
  • Adding New Data - Append/Concat
  • Final Project & End Note
Machine Learning Syllabus:
Machine Learning

About Machine Learning Course
Installation of Anaconda
What is Machine Learning
Types of Machine Learning, Supervised Learning and Regression
Types of ML,Logistic Regression and Unsupervised Learning
SVM -What is SVM and How do they work
SVM-Loading and Examining our dataset
SVM-Building and Tweaking our SVM Classification mode
What is Decision Tree?
Building the Decision Tree : Decision Tree Learning
Building a Decision Tree - Information Gain a Gini Impurity
Decision Tree Lab:Building our First Decision Tree
Decision Tree Lab:Viewing and Tweaking our Decision Tree
What is Overfitting
Random Forest Lab
Teamwork
Avoiding Overfitted Models

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