# Data Science Internship: TV Sales Prediction

Rated

5

(Out of 5)

Orientation on:

100,000+ Participants

have chosen our platform to learn coding.

1999
2500

Rated

5

(Out of 5)

00
Days
00
Hrs
00
Min
00
Sec

## Data Science Internship: TV Sales Prediction

Starts From:
Tutorials:
10
Duration:
4 weeks
Starts From:
Duration:
4 weeks
Eligibiliity:
Early Bird Price:
1999
2500
Orientation:

In this internship, you will use simple linear regression to predict the expected sales of a Television company.

Sales expectations of any television company can be based on a variety of factors, such as market trends, past sales performance, and the business's growth plans. In order to have a real life experience you will deal with majority of these factors while setting up your model.

Sales expectations are important for a business because they provide a target for the sales team to strive towards, and they help the business plan and allocate resources. Having clear sales expectations allows the business to set goals and create a roadmap for achieving those goals. It also helps the business to track its progress and make adjustments as needed to stay on track.

For businesses, it's important to estimate how many sales are likely to happen, depending on a given advertisement strategy. By setting and tracking sales expectations, a business can improve its chances of success and avoid costly mistakes. It is your turn to do that now.

Tools you will learn in this internship:

Simple linear regression - It widely used statistical technique for modeling the relationship between a dependent variable and one or more independent variables. It assumes that the relationship between the dependent and independent variables is linear, meaning that a change in the independent variable leads to a constant change in the dependent variable. This assumption makes linear regression easy to understand and interpret, and it allows for fast and efficient calculation of the model parameters.

Numpy - This library is used in Python for scientific computing because it provides tools for working with large and complex arrays of data. It allows for efficient manipulation of the data, and it supports a wide range of mathematical operations on the data. NumPy is particularly useful for working with numerical data, such as data from scientific experiments or financial data. It is also fast and memory-efficient, making it well-suited for working with large datasets.

Pandas - This library is used in Python for data manipulation and analysis because it provides tools for working with tabular data, such as data stored in a table with rows and columns. Pandas allows for easy manipulation of the data, such as filtering, aggregation, and transformation, and it also provides tools for reading and writing data to and from a variety of formats.

Sci-kit - This library is used in Python for machine learning because it provides a wide range of algorithms for supervised and unsupervised learning, and it is built on top of NumPy, SciPy, and Matplotlib. This makes it easy to use scikit-learn within a broader data analysis workflow, and it allows for efficient manipulation of the data and powerful visualization of the results.

# Skills you can learn in this course

Data Science
pandas
numpy

## Instructors

Aneeq

Aneeq Dholakia has trained thousands of students from tier 2/3/4 colleges and helped them achieve their dream companies. Aneeq excels at training for competitive programs like TCS, CodeVita, HackWithInfy and product companies like JP Morgan, ServiceNow, Adobe, Amazon and more.

Shubham

Shubham Lal, is a Software Developer (SDE-2 ) at Microsoft who has mentored 5,000+ students and has been invited as a speaker in 20+ events. As an instructor, Shubham has worked with leading EdTech's in India.

## Verifiable Certificate

You can share your Internship Certificate in the certifications section of your LinkedIn profile, on printed resume or other documents.

All certificate images are for illustrative purposes only and may be subject to change at the discretion of Edyst

## You Will Get :-

Joining Letter
Internship Report
(as per AICTE guidelines)
Certificate of Completion
Guidance on how to explain project to interviewer
Guidance on how to put project in resume
Doubt clearing session
Exclusive guidance from industry mentor
*Orientation -

## Key Programme Takeways:-

Increase interview call, internship experience letter + internship joining letter + internship evaluation report (as per AICTE guidelines)
You’ll learn the easiest way to get rid of problems comes in data cleaning
Plan and implement appropriate machine learning techniques in a simulated environments
Leverage insights from the data to reach conclusions and showcase your enhanced skill set on LinkedIn and GitHub profile.
Maximize engagement on new projects and work with CSE students from different colleges.

## Why Edyst?

Other Platforms
Internship Evaluation Report
AICTE guidelines based internship evaluation report
No report
Curriculum
Designed by an industrial trainer working as SDE-2 at Microsoft with 5+ experience
Designed by a non-industrial trainer
Joining Letter & Experience Letter
No joining letter is provided
Lifetime association with Edyst - #1 Careers Community in India
Associated with a non credible institution
Credibility of Faculty
Learn from experts from top tech. globally famous product firms
Faculty working in less known IT service firm
Placement
100,000+ students have crack off campus interviews using our courses - check our students video testimonials below
No placement / reviews

## Career Services

Building an Impressive Project
Building an Impressive GitHub Profile
Internship Experience
Project Explaining Guidance

## Vaishnavi

Placed in
ServiceNow
-
24 LPA

Edyst's training style completely resonated with me. I approached programming as more than a subject. Thanks to Edyst team for the guidance!

## Sakila

Placed in
-
12 LPA

I started practising on Edyst platform since my 3rd year of college focused on placements & always liked the way they helped us when we were stuck at a particular problem.
Thank you, Edyst for all the assistance and amazing support!

## Sriram

Placed in
Seawise Capital
-
8 LPA

When I joined the Edyst courses I received personalized mentoring on how to crack coding rounds of different companies. Through a combination of coding skills and great projects, I received multiple offers above 6+ lakhs per annum. Finally I joined for 8+ Lakhs package. Thanks for all the support, from Edyst Team.

## Harika

Placed in
DBS
-
7 LPA

I feel the best thing about edyst is its company-specific guidance and the huge problem sets covering up almost all the concepts from beginner to advanced concepts, it helped me a lot for my placement preparation

## Raviteja

Placed in
EPAM
-
6 LPA+

Edyst platform has helped me enhance my skills and problem solving ability. Some of the tips shared by them helped me to clear the coding round & interview effectively.
Thank you for this opportunity, Edyst!

## Dileep

Placed in
TCS Digital
-
7 LPA+

Being a mechanical student and getting into an IT company is very tough. One of the main reason I could able to crack TCS CodeVita is because of Edyst.
Aneeq sir, your doubt clearing sessions, daily assignments & incredible mentors support really brushed up my skills.

## Rahil Sayed

Placed in
FIS Global
-
8.6 LPA

I really like the Company specific practice questions they turn out to be super helpfulduring my interview, I didn't face any difficulty, the variety and range of practice questions (especially on arrays) got me my dream job. Also, the online live session were very interactive and helped me in revision and solving doubts. Thank you Edyst.

## Sai Sasikanth Rokkam

Placed in
Deloitte
-
7.6 LPA

I wanted video lectures along with the coding assessments and that is exactly what Edyst offered me. I also got the roadmap towards getting a good placement job, I can't thanks Edyst enough for my success.

Placed in
Concentrix Catalyst
-
5 LPA

About Edyst, I like the most is the explanation given by mentor using real life examples. Mentors helped me with solution to each and every problem I had. I am glad that I joined Edyst, thank you for offering the good and relevant practice excercises.

## Janhavi

Placed in
Cognizant
-
4 LPA

For me the 3 feature of Edyst, changed my life1.Live mentor support - I used this to ask my doubts from mentor and learned a lot about coding.2.Practice assessments - I used this to check my learning skills3.Leaderboard and daily streak - It helped e to stay consistent, sometime I felt jealous of my friends for securing a rank above me for the particular week.

*Orientation -

## Our Alumni are Working at

50+ Companies

Note: All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

Price:
1999
2500
00
Days
00
Hrs
00
Min
00
Sec

## Vaishnavi

Placed in
ServiceNow
-
24 LPA

Edyst's training style completely resonated with me. I approached programming as more than a subject. Thanks to Edyst team for the guidance!

## Sakila

Placed in
-
12 LPA

I started practising on Edyst platform since my 3rd year of college focused on placements & always liked the way they helped us when we were stuck at a particular problem.
Thank you, Edyst for all the assistance and amazing support!

## Sriram

Placed in
Seawise Capital
-
8 LPA

When I joined the Edyst courses I received personalized mentoring on how to crack coding rounds of different companies. Through a combination of coding skills and great projects, I received multiple offers above 6+ lakhs per annum. Finally I joined for 8+ Lakhs package. Thanks for all the support, from Edyst Team.

## Harika

Placed in
DBS
-
7 LPA

I feel the best thing about edyst is its company-specific guidance and the huge problem sets covering up almost all the concepts from beginner to advanced concepts, it helped me a lot for my placement preparation

## Raviteja

Placed in
EPAM
-
6 LPA+

Edyst platform has helped me enhance my skills and problem solving ability. Some of the tips shared by them helped me to clear the coding round & interview effectively.
Thank you for this opportunity, Edyst!

## Dileep

Placed in
TCS Digital
-
7 LPA+

Being a mechanical student and getting into an IT company is very tough. One of the main reason I could able to crack TCS CodeVita is because of Edyst.
Aneeq sir, your doubt clearing sessions, daily assignments & incredible mentors support really brushed up my skills.

## Rahil Sayed

Placed in
FIS Global
-
8.6 LPA

I really like the Company specific practice questions they turn out to be super helpfulduring my interview, I didn't face any difficulty, the variety and range of practice questions (especially on arrays) got me my dream job. Also, the online live session were very interactive and helped me in revision and solving doubts. Thank you Edyst.

## Sai Sasikanth Rokkam

Placed in
Deloitte
-
7.6 LPA

I wanted video lectures along with the coding assessments and that is exactly what Edyst offered me. I also got the roadmap towards getting a good placement job, I can't thanks Edyst enough for my success.

Placed in
Concentrix Catalyst
-
5 LPA

About Edyst, I like the most is the explanation given by mentor using real life examples. Mentors helped me with solution to each and every problem I had. I am glad that I joined Edyst, thank you for offering the good and relevant practice excercises.

## Janhavi

Placed in
Cognizant
-
4 LPA

For me the 3 feature of Edyst, changed my life1.Live mentor support - I used this to ask my doubts from mentor and learned a lot about coding.2.Practice assessments - I used this to check my learning skills3.Leaderboard and daily streak - It helped e to stay consistent, sometime I felt jealous of my friends for securing a rank above me for the particular week.

*Orientation -

## Course Syllabus

Revision of Python:

1. Data Types in Python
2. Arithmetic operations
3. Loops and Iterations
4. Comprehensions
5. Functions in Python
6. Map, Filter, and Reduce Functions
7. Lists
8. Tuples
9. Sets
10. Dictionaries

Numerical Python (NumPy)

1. Introduction to NumPy
2. Basics of NumPy
3. Operations over 1-D Arrays
4. Multidimensional Arrays
5. Creating NumPy Arrays
6. Mathematical Operations on NumPy
7. Mathematical Operations on NumPy II
8. Computational Times in NumPy vs Python Lists

Pandas

1. Introduction to Pandas
2. Basics of Pandas
3. Pandas - Rows and Columns
4. Describing Data
5. Indexing and Slicing
6. Operations on DataFrames
7. Groupby and Aggregate Functions
8. Merging DataFrames
9. Pivot Tables

Exploratory Data Analysis

1. Introduction to Univariate Analysis
2. Categorical Ordered/Unordered Univariate Analysis
3. Statistical on Numerical Features
4. Correlation vs Causation
5. Multivariate Analysis

Data Visualisation (Matplotlib)

1. Introduction to Matplotlib
2. The Necessity of Data Visualisation
3. Visualisations - Some Examples
4. Facts and Dimension
5. Bar Graph
6. Scatter Plot
7. Line Graph and Histogram
8. Box Plot
9. Subplots
10. Choosing Plot Types

Simple Linear Regression

1. Introduction to Machine Learning
2. Regression Line
3. Best Fit Line
4. Strength of Simple Linear Regression
5. Assumptions in SLR
6. Hypothesis Testing in LR
7. Building a linear model
8. Residual Analysis and Predictions
9. Linear regression using SKLearn

Problem Solving, Presentation and Story Telling

1. TV Sales Prediction: Case Study
2. Prediction vs Projection
3. EDA
4. Model Building
5. Assessing the Model
6. Interpreting the results

Is there any fee for the internship?
Can I get a discount on the internship fee?
Are the internship sessions live or recorded?
Is there any prerequisite to joining this internship?
What is the difference between this internship and a course?
Are Working professionals eligible for this internship?
Do we teach Data science?
By when should I complete this?
Is there any placement guarantee?
On which technology the internship is based?

Starts From:
Duration:
4 weeks
Eligibility: