linear regression assignment upgrad github

Instantly share code, notes, and snippets.

AnaganiVaralakshmi / SIMPLE LINEAR REGRESSION ASSIGNMENT 4 DELIVERY.ipynb

• Star 0 You must be signed in to star a gist
• Fork 0 You must be signed in to fork a gist
• Embed Embed this gist in your website.
• Share Copy sharable link for this gist.
• Clone via HTTPS Clone using the web URL.
• Learn more about clone URLs

Executive PG Program in Data Science

In association with

With Industry Experts From

Paid learners, recommended 12-15 hrs/week, programme overview, key highlights.

3 Unique Specializations to choose from - Deep Learning - Business Intelligence/ Data Analytics - Data Engineering

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects

Choose from 3 specializations, receive industry mentorship, dedicated career support, learn 14 programming tools & languages & much more

3 Unique Specializations

Choose from 3 specializations as per your background & career aspirations. Get an Executive PG Program in Data Science from IIITB with a specialization.

Dedicated Career Assistance

Receive 1:1 career counselling sessions, resume building sessions and mock interviews. Utilise the projects in the course to build your profile on platforms like GitHub.

Student Support

Support available all days for 24 hours. For urgent queries, use the Call Back option on the platform.

Top Skills You Will Learn

Advance your career, who is this program for, minimum eligibility, programming languages and tools covered.

IIIT Bangalore

• Connect with a global network of accomplished IIITB Alumni
• Widely recognized and valued Executive PG Program in Data Science
• Network with Data Science professionals across all industries

Instructors

Learn from india’s leading data science faculty and industry leaders.

Hindol Basu

Chandrashekar Ramanathan

Tricha Anjali

Sameer Dhanrajani

Debabrata Das

Prof. G. Srinivasaraghavan

Ujjyaini Mitra

Dinesh Babu Jayagopi

Kalpana Subbaramappa

Sajan Kedia

Mirza Rahim Baig

Bijoy Kumar Khandelwal

Course 1 - data toolkit.

• Introduction to Python
• Programming in Python
• Python for Data Science
• Data Visualization in Python
• Exploratory Data Analysis
• Credit EDA Case Study
• Inferential Statistics
• Hypothesis Testing
• Data Analysis using SQL
• Advanced SQL & Best Practices
• SQL Assignment: RSVP Movies

Course 2 - Machine Learning-I

• Linear Regression
• Linear Regression Assignment
• Logistic Regression
• Classification using Decision Trees
• Unsupervised Learning: Clustering
• Basics of NLP and Text Mining
• Business Problem Solving
• Case Study: Lead Scoring

Specialisation - Data Analytics

• Data Modelling
• Advanced SQL Programming
• Introduction to Cloud and AWS
• Analytics at Large Scale in Spark - I
• Analytics at Large Scale in Spark - II
• Big Data Case Study
• Basic Viz. using Tableau
• Advanced Excel
• Data Analysis and Visualisation in PowerBI
• Analytical Thinking and Structured Problem Solving using Frameworks
• Data Storytelling
• AirBnB Case Study
• Data Structures and Algorithms
• Searching and Sorting
• Algorithm Analysis + Recursion
• Advanced Database Programming using Pandas
• Python & SQL Lab

Specialisation - Business Analytics

• Bagging & Random Forests
• Model Selection - I
• Model Selection - II
• Time Series Forecasting - I
• Time Series Forecasting - II
• Model Selection
• Airbnb Case Study
• "Fundamentals of Transformers Architecture, Generative AI, ChatGPT & Prompt Engineering using Non Reasoning, Chain of Thought & Advanced Techniques"
• Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
• Integrating speech using Whisper API and application deployment using Flask
• "Fundamentals of Design, Photography, Product Development using Stable Diffusion in Python & Create PixxelCraft AI to enable fast-track digitisation for offline e-commerce businesses by generating high-quality images AI for a large product portfolio"
• "Applications of LLMs in Data Science Projects & Automating News Recommendation using GPT3 and Copilot powered Machine Learning applications of LLMs"
• Interview Gynie AI: Chatbot Development Project

Specialisation - Deep Learning

• Bagging & Random Forest
• Principal Component Analysis
• Advanced Regression + Time Series Forecasting (Optional)
• Advanced ML case Stuy
• Introduction to Neural Networks and ANN
• Backpropogation & Hyperparameter Tuning in Neural Networks
• Introduction to Convolutional Neural Networks
• CNN Architectures and Industry Applications + Recurrent Neural Networks (Optional)
• Applications of DL in CV: Object Detection Image Segmentation (Optional)
• Gesture Recognition Case Study

Specialisation - Natural Language Processing

• Advanced ML
• Neural Nets for NLP
• Syntactic Processing
• Introduction to Semantic Processing & Distributional Semantics
• Semantic Processing - Topic Modelling
• Advanced DL in NLP: Attention Mechanism Automatic
• Ticket Classification
• Fundamentals of Transformers Architecture, Generative AI, ChatGPT & Prompt Engineering using Non Reasoning, Chain of Thought & Advanced Techniques
• Fundamentals of Design, Photography, Product Development using Stable Diffusion in Python & Create PixxelCraft AI to enable fast-track digitisation for offline e-commerce businesses by generating high-quality images AI for a large product portfolio
• Applications of LLMs in Data Science Projects & Automating News Recommendation using GPT3 and Copilot powered Machine Learning applications of LLMs

Specialisation - Data Engineering

• Data Management and Relational Database Modelling
• Introduction to Cloud and AWS Setup
• Introduction to Hadoop and MapReduce Programming
• NoSQL Databases and Apache HBase
• Data Ingestion with Apache Sqoop and Apache Flume
• Map reduce Programming Assignment
• Hive and Quering + Optional Assignment
• Introduction to Apache Spark+ Optional Assignment
• Amazon Redshift
• ETL Project
• Optimizing Spark for Large scale processing
• Real-Time Data Streaming with Apache Kafka
• Real-Time Data Processing using Spark Streaming + Assignment (Optional) + Apache Flink (Optional)
• Building Automated Data Pipelines with Airflow
• Analytics using PySpark+ Optional Assignment
• Retail Project

Specialisation

Topics covered, data analytics, industry projects.

• Engage in collaborative projects with student-mentor interaction
• Benefit by learning in-person with expert mentors
• Personalized subjective feedback on your submissions to facilitate improvement

IMDb Movie Analysis

Analyze movie data from the past hundred years and find out various insights to determine what makes a movie do well.

Uber Supply-Demand Gap

Use analytics to identify why Uber sometimes faces a supply-demand challenge and what can be done to overcome it

Creditworthiness of Customers

Learn how Predictive Analytics can be used to decide the creditworthiness of customers and whether they are issued a credit card or not

Lead Scoring

Learn how the knowledge of basic machine learning algorithms can be used to determine leads that are potentially convertible and save your Sales team time, money, and resources.

Fraud Detection

Decline fraud transactions on a credit card in real-time to minimize the losses so that customers are not charged for items that they did not purchase.

Speech Recognition

Learn how Google speech-to-text works and make your own model using deep learning.

Image Captioning

Build a model which will caption a given image and describe it in sentences in a detailed way like objects present, the actions they are doing, etc.

Gesture Recognition

Learners will build a gesture recognition model for a Smart-TV to recognize 5 hand gestures, using a 3D Convolution Network.

Social Media Listening

What if you could predict the popularity of a brand like upGrad in India?

Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them.

Retail-Giant Sales Forecasting

Help a retail-giant to have a clear idea of how their sales will look like in the future.

Interactive Marketing Campaign Analysis

Research and analyse data from a marketing campaign to gain valuable insights and determine the ‘yays’ and ‘nays’ of the campaign.

The upGrad Advantage

Learning support.

• Receive unparalleled guidance from industry mentors, teaching assistants and graders
• Receive one-on-one feedback on submissions and personalized feedbacks on improvement
• Support is available all days for 24 hours.
• For urgent queries, use the Call Back option on the platform.

Doubt Resolution

• Timely doubt resolution by Industry experts and peers
• 100% Expert-verified responses to ensure quality learning
• Personalized expert feedback on assignments and projects
• Regular live sessions by experts to clarify concept related doubts

• Live sessions by experts on various industry topics
• One-on-one discussion and feedback sessions with industry mentors

Our Learners Work At

Admission Process

There are 3 simple steps in the Admission Process which is detailed below:

Take the Online Eligibility Test

Complete your application to take the 17-minute online eligibility test with 11 questions to kick-start the admission process. The test is designed to assess your quantitative & logical aptitude ensuring you're ready for the program.

Get Shortlisted & Receive your Offer Letter

Our Admissions Committee will review your test score & profile. Upon qualifying, an Offer Letter will be sent to you confirming your admission to the Executive PG Program in Data Science.

Block your Seat & Begin the Prep Course

Block your seat with a payment of the enrolment deposit to enrol into the program. Begin with your Prep course and start your Data Science journey!

Program Fees

₹ nan ( no taxes applicable ) *.

Refer someone you know and receive cash reimbursements of up to $500!*

*More details under the referral policy under Support Section

Student Reviews

Vibhor Srivastava

Rutuja Mowade

Anshu Srivastava

Gangadhar Mathyam

Arindam Banerjee

Empowering learners of tomorrow.

Over 2,300 students have completed this course and started working at their dream job, whats stopping you?

Frequently Asked Questions

Course curriculum, what is the executive pg program in data science from upgrad.

The Executive PG Programme in Data Science is an engaging yet rigorous -- month online program designed specifically for working professionals to develop practical knowledge and skills, establish a professional network, and accelerate entry into data science careers. The certification is awarded by IIIT Bangalore.

What should I expect from the Executive PG Program in Data Science?

Expect to carry out several industry-relevant projects simulated as per the actual workplace, making you a skilled data science professional at par with leading industry standards.

What should I NOT expect from the Executive PG Programme in Data Science?

The programme is NOT going to be easy. It will be requiring at least 12-15 hours of time commitment per week, applying new concepts and executing industry relevant projects.

Which topics are going to be covered as part of the program?

The programme is designed for working professionals looking for a transition or growth into the data domain. Considering the requirements of different data roles in the industry, the curriculum is divided into six tracks. The course will have a common curriculum running for approximately for the first 5-6 months that everyone will go through after which they have to do any of the 6 specialization and a capstone project, in the remaining 6-7 months. The topics that are going to be covered as a part of the common curriculum and each of the six specializations are as follows:

Common Curriculum: Basics of SQL, Python, Statistics and EDA, Basic Machine Learning Models

Deep Learning Specialization: Advanced Machine Learning, Neural Networks

Business Intelligence: Advanced SQL and NoSQL Databases, Storytelling with Advanced Visualization

Data Engineering: Data Modelling and Data Warehousing, Building Data Pipelines, Data Streaming and Processing

What type of learning experience should I expect?

The content will be a mix of interactive lectures from industry leaders as well as world-renowned faculty. Additionally, the program comprises live lectures or hangout sessions dedicated to solving your academic queries and reinforcing learning. 

Is any certification granted at the end of the programme?

Post successful completion of the program, a certificate in Executive PG Program in Data Science would be granted from IIIT Bangalore.

When will I have to choose my specialization track?

The programme has ~23 weeks of common curriculum and ~29 weeks of the specialization and capstone project. Once you’re through the 23 weeks of curriculum common to all the three tracks, you will be prompted to choose your specialization.

How do I know which specialization is the best for me?

When you’re nearing the end of your common curriculum, upGrad will provide you with a recommendation best suited for you based on your background. The following mapping should give you an idea about the specialization best suited for you although the final upGrad recommendation would come from a much more exhaustive rule engine.

- Deep Learning: Engineers, Software and IT Professionals

- Business Intelligence/ Data Analytics: Engineers, Marketing and Sales Professionals, Freshers

- Data Engineering: Software and IT Professionals

Do I have to choose the specialization recommended by upGrad?

No. You can choose whatever specialization you like once you are through the common curriculum. However, we would urge you to take up the recommendation provided by us as this based on a sophisticated rule engine and is meant to give you the best outcome for your background which will, in turn, make it easier for you to switch to a data role.

Time Commitment

What is the time commitment expected for the program.

At least 12-15 hours per week of time commitment is expected to be able to graduate from the program.

Will each specialization require different time commitments?

Each of the six specializations will have a common ~23-week curriculum in which the time commitment will be exactly the same. When you move onto a specialization, it might be that some weeks are heavier in a particular track but lighter for the others. But, overall the total time commitment required will be 12-15 hours/week on average.

Career Prospects and Support

What type of career support should i expect from this program, how will my doubts/questions be addressed in an online program, will i receive special different career services in each specialization.

Each specialization is designed to give you the best outcome based on your background and help you industry experts in the data domain. The services and support for all the tracks will remain the same. Every student will have live sessions, industry mentorship and preparatory support according to the requirements in their specialization track.

Refund Policy/Financials

Is there any deferral or refund policy for this program.

Refund Policy: (Programs with/without prep-session component)  

• The student must pay applicable caution money for the enrollment of the course. This will be adjustable against the total course fee payable by the student.
• You can claim a refund for the amount paid towards the Program at any time, before the Program Start Date, by visiting www.upgrad.com and submitting your refund form via the "My Application" section under your profile. You can request your Admissions Counsellor  to help you in applying and withdrawing for a refund by sending them an email with reasons listed. There shall be no refund applicable once the program has started. This is applicable even for those students who could not complete their payment, and could not be enrolled in the batch opted for. However, the student can avail pre-deferral as per the policy defined below for the same.
• Refund shall be processed to an eligible student within 30 working days from the date of receipt of refund form subject to the submission of the right documents from him/her in this regard.
• Refund shall be subject to deduction of $150 processing charges and as per the conversion rate applicable.

Deferral Policy: (Post Program Commencement)  

• If a student is facing severe issues in dedicating time to the course, we provide the opportunity for the student to defer to another batch. This deferral will be subjected to a 10% deferral fee of the total course amount + taxes if any along with the differential program fees between the two cohorts.
• This deferral request shall be granted only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch in which the student was originally enrolled.
• The deferral request will be approved once the deferral fee is paid. Until the process is completed, the student will be assumed to be continuing in the same cohort.
• The student has 7 days (including holidays and weekends) from the date of deferral request to make the payment of the deferral fee post which the deferral request shall be deemed as expired, and the student shall continue as part of the current cohort.
• If the student completes the deferral payment, the student’s login will be disabled, the student will leave the deferred cohort and the student will start learning on the new cohort from the point of the last assignment that was graded in the deferred cohort. All grades and progress till that point will be carried forward as it is to the new cohort. For clarification, the grades of the graded assignments will be carried forward, whether or not the student had submitted these grading during the initial stage.
• The deferral can only be requested during the batch for which the student has enrolled is ongoing. Once the batch has completed, deferral requests shall not be entertained. For clarification, the batch completion here shall mean the “last grace deadline” as communicated by upGrad.

Deferral Policy: (Pre- Program Commencement)  

• If a student, due to unavoidable circumstances is unable to commence with the cohort and requests for a deferral before the cohort starts, we provide the opportunity for the student to defer to another batch.
• However, the student will be required to pay 50% of the total course fee amount (inclusive of taxes) before the deferral can be approved. Till this is completed, the student will be assumed to be continuing in the same cohort.
• A student can request for deferral only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch in which the student was originally enrolled.
• The student shall have time till the current cohort launch date to make the payment of the 50% program fee, post which the deferral request will expire. In the event the student raises a refund request after the deferral window expires, the above-mentioned applicable refund policy shall apply.
• The fee applicable to the deferred student will be as per prevailing fee for the batch student has opted to defer to (No additional deferral fee is required to be paid). The student shall be liable to pay the differential program fees between the two cohorts if any.

Selection Criteria

How do i know if the program is right for me.

If you like finding meaningful insights from data and if you get excited by the prospect of informing business decisions through analysis and have an analytical bend of mind, then this program is meant for you. As long as you are able to clear the selection test (or are exempt) and are excited about the transition to Data Science, this program is meant for you.

My current role does not include exposure to data. Does it make sense for me to opt for this program?

What is the application process for the program and what are the timelines.

You can start the application process by submitting the application. Applications have already started for the next cohort.

What is the selection process for this program?

upGrad, IIITB, world-renowned faculty, and many industry leaders have committed a lot of time in conceptualising and creating this program to make sure that the learners can receive the best possible learning experience in data analytics. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for Data Science.

The applicants will have to take a selection test designed to check their aptitude and quantitative abilities. The applicants can skip the test if they meet one of the following criteria:

• GRE score is greater than 300
• GMAT score is greater than 650
• CAT score is greater than 90 percentile
• GATE score is greater than 500

Is there any minimum educational qualification required to take this program?

To be eligible for the program, the following criteria need to be fulfilled:

• College Degree: The applicant should have a bachelor’s degree in science/engineering/business administration/commerce/mathematics or masters in mathematics/statistics with 50% or equivalent passing marks.
• Work experience: The applicant should preferably have at least 1-2 year of professional experience.

upGrad Learner Support

Multiple_Linear_Regression_Bike_Sharing_Assignment

Problem statement:.

A US bike-sharing provider BoomBikes has recently suffered considerable dips in their revenues due to the ongoing Corona pandemic. The company is finding it very difficult to sustain in the current market scenario.In such an attempt, BoomBikes aspires to understand the demand for shared bikes among the people after this ongoing quarantine situation ends across the nation due to Covid-19. They have planned this to prepare themselves to cater to the people's needs once the situation gets better all around and stand out from other service providers and make huge profits.

The company wants to know:

• Which variables are significant in predicting the demand for shared bikes.
• How well those variables describe the bike demands
• Develop a model to find the variables which are significant the demand for shared bikes with the available independent variables.
• It will be used by the management to understand and manipulate the business strategy to meet the demand levels and meet the customer's expectations.

Step1: Importing Libraries

UpGrad Data Science Industry Projects

Real-life industry projects with code and documents.

Photo by Austin Distel on Unsplash

UpGrad Industry Projects list :

This all Projects are in Data Science Programme of UpGrad

• IMDb Movie Analysis
• Credit EDA Case Study
• Bike sharing systems (Linear Regression Assignment)
• Lead Scoring
• Clustering Assignment
• Telecom Churn
• Fraud Detection
• Retail-Giant Sales Forecasting
• RSVP Movies (SQL Assignment)
• Hive Case Study
• ETL Project
• Assignment - Structured Problem Solving
• IPL Visualisation
• NYC Parking: EDA using Apache Spark
• MapReduce Programming Assignment
• Business Case Study - Staff Planning

Project Reference's : upgrad.com/data-science-pgd-iiitb

Explore More Projects :

Youtube Channel : youtube.com/channel/UC-fiWBgdArpy9KtC_CO7Xr..

Website : Final-Project

Contact for Code, PPT, Synopsis, Report and Explanation Video HD is available for above projects.

💬 Mail : [email protected]

💬 Whatsapp : +91 9310631437 : Chat

Thank you :)