Data Science :
Research & Operations.
60 Days Training + Internship.

Here’s an internship with a sense of purpose that will prepare you for your future as a Data Scientist. In only 60 Days, you will be confident with using the tools used by Data Scientists to tackle challenges and complete various life saving tasks for the company’s survival!

Apply for Financial Aid Here.

New Year 2022


Registration Fee includes everything in this program.

Courses, Trainings, Projects, Webinars and Certificates.

We accept international applications, WhatsApp us for queries.

With 4.5 stars on Trustpilot, and plethora of happy students, we are sure you will be satisfied with the training. You get a 7 days money back guarantee with this course, you can access the material for 7 days and if you have issues with the training, we will refund your complete course fee.


We are serious about making this training the best Data Science training at an amazingly affordable rate.

About the program.

Data Science : Research & Operations Training + Internship is a 60 day program is a completely online program in which you will be taught Data Science and will be given projects based on what you've learnt. This internship is perfect if you're interested in becoming a Data Scientist or having an interest into starting or restarting your career in this field.

This internship will give you the skills to be a fresher Data Scientist in 60 days. You'll learn how to collect, store, visualize, process, and use statistics to get valuable insights from data using various tools like Python, R, SQL, MS Excel as well as data visualization tools like Matplotlib and Seaborn.

Training cum Internship ?

In this Training cum Internship program. As we teach and train you, we will parallelly give you projects to do based on what you've learnt; the course will count towards the training whereas the projects will count towards the internship. So you get a "Certificate of internship" and a "Certificate of Training" that you took for the internship.

The intern learns data science skills while working on fun projects which they can add to there resume and LinkedIn profiles and also take back to show in their university, job or future internships.

Interested? Join us as an intern today!

Placement Assistance?

See, Placement Assistance is an alluring term used by E-Learning platforms. They use this to attract you.

Those e-learning platforms will forward your resumes to their partner agencies, who will then call you for an interview - here, the placement assistance gets completed.
Now in the interview, they either reject you or give you a 2-3LPA package to work in a far different field from the actual Data Science.

What do we do then?

We train you and make your work on industry-standard Data Science projects. So that you don't need any kind of assistance whatsoever, you can walk into interviews and get an advantage over the other applicants there. We also forward your resume to several companies which may invite you for a direct interview.

Moreover, a "Certificate of Distinction" is provided to the best performers based on various assessment parameters that you can show to your interviewers as an achievement.
The top 3 performers also gets a chance to join College Finder as part-time/full-time Data Operator, Analyst or Scientist with handsome salaries and experience certificates.

Available Certificates :

All interns will get a “Certificate of Internship” which will state about your internship with us. To get this certificate you must complete all the compulsory projects given to you by the instructors.

A student will get a “Certificate of Completion” if he/she has completed all the modules of the training and his/her quiz scores are above 70% for all the quizzes.

A “Certificate of Distinction” is based on various different factors of a student. It is provided to the top performing students who has more than 90% average quiz marks and has completed and submitted all the projects. And is found actively helping other interns.


hours video content


tools covered


hands-on Projects


Live Support

What You'll Learn :

    • On the first day you will get complete information about the Curriculum & Classes.
    • What is Data Science? What does a data scientists do?
    • The need for data science / Problems solved with Data Science.
    • Big Data
    • Difference between AI, ML and DL
    • How tech giants use data (for customer preferences).
    • How does Netflix and Amazon use data to build their recommendation model.
    • The Companies using Python. Popular Applications where Python is used.
    • Python Environment Setup (Jupyter).
    • Fundamentals: Variables, Numbers and Boolean, Strings, Arithmetic Operators, The Double Equality Sign, Reassign Values, Add Comments, Line Continuation, Indexing Elements, Structure Your Code with Indentation, Comparison Operators, Logical and Identity Operators.
    • Data Types: Immutable – [Numbers, Strings, Tuples]; Mutable – [Lists, Dictionaries, Sets] and related operations.
    • Loops: For Loops (break, continue, pass) & While Loops
    • Functions: creating and calling functions, lambda, filter, map, in-built functions, user defined functions
    • Condition: if, if-else, nested if-else, else-if
    • Library: What is library, what is package, how to create packages, Introduction to PIP, Namespace, Using Python Packages, Installing Packages via PIP
    • An intro to NumPy : Few related operations
    • Mathematical computing with Python (NumPy)
    • Array: Data Types in an Array, Dimensions of an Array, Operations on Array: Indexing, Slicing, Splicing, Sub-setting
    • PandasPandas Setup & Intro, Loading Data into Pandas, Reading Data, Sorting Values, Adding or Removing Columns, Rearranging Columns, Saving Data, Filtering Data, Filtering Based on Textual Patterns, GroupBy, Chunksize, DataFrame, Panel, Reindexing, Iteration, Sorting, Working with Text Data, Merging/Joining, Concatenation, Date Functionality, Categorical Data
    • Introduction: Introduction of R, R Installation, Basic Structure of R program with a simple program, Constants, variables and declarations, Simple Input-Output statements, Operators – Arithmetic, Relational and Logical
    • Data Types in R: What are datatypes in R?, Types of data types in R, Numeric Datatypes, Integer Datatypes, Logical Datatypes, Complex Datatypes, Character Datatypes, Vectors Datatypes, List Datatypes, Matrices Datatypes, Arrays Datatypes, Factors Datatypes, Data Frames in R
    • Variables in R: Variables Definition, Declaring and Initialising variables, Syntax of declaring variables, Important method for variables, Scope of variables, Dynamic scoping in R Variables, Lexical scoping in R variables, Data type of a variable, Finding variables, Deleting variables
    • Control Flow: Control statement in R program, What are control statements, If conditions, If-else conditions, For Loop, Nested Loop, While loop, Repeat loop and break statements, Return statements, Next statement, Decision making in R prog with flow chart, Switch case in R, For loop in R, While loop in R, Repeat loop in R, Go to statements in R, Break and next statements in R
    • Functions: Function Definition, Function components, Built-In functions, User defined functions, Single input- single output, Multiple Input – Multiple Output, Inline function, Passing arguments of a function, Lazy evaluation of a function, Function argument in R programming, Adding an argument in R, Adding multiple arguments in R, Adding default arguments in r, Dots arguments, Function as an argument, Type of function in R programming, How to define a function?, Calling a function, Types of function, Primitive function, Infix function, Replacement function, Recursive function, Application of recursive function in R programming, Conversion of function.
    • Data Structures: What are data structures in R programming?, R-Strings, R-Vectors, R-List, R-arrays, R-Matrices, R-Factors, R-Data frames
    • R- Object Oriented Programming: Classes and Objects, Creating S3 class, Generic function, Attributes, Classes in R programming, R-Objects, Encapsulation in R programming, Polymorphism in R programming, R-Inheritance, Abstraction in R programming
    • Error Handling: Handling error in R Programming, Condition handling in R program, Debugging in R program
    • File Handling: File handling in R Programming, Reading files in R Programming, Writing files in R Programming, Binary files in R Programming
    • Data Interfaces: Data Handling in R Programming, Importing data in R Programming, Exporting data in R Programming, Working with CSV files in R Programming, Working with XML files in R Programming, Working with EXCEL files in R Programming, Working with JSON files in R Programming, Working with DATABASES in R Programming
    • R-Statistics
    • Mean, median and mode in R programming
    • Calculate the average, variance and standard deviation in R Programming
    • Descriptive analysis in R Programming
    • Normal distribution in R Programming
    • Binomial distribution in R Programming
    • ANOVA test in R Programming
    • Co-Variance and Correlation in R Programming
    • SKEWNESS and KURTOSIS in R Programming
    • Hypothesis testing in R Programming
    • Bootstrapping in R Programming
    • Time series analysis in R Programming
    • What is Machine Learning?
    • Phases, Advantages, Applications and Types of Machine Learning
    • Supervised Learning in Depth
    • Introduction to Different Algorithms of Regression & Classification
    • Evaluation Metrics of Regression & Classification
    • Model Flow in Machine Learning
    • Creating a Machine Learning Model
    • Different types of data
    • Types of Statistical Analysis
    • Z Test, T Test, Chi-Square Test
    • Understanding Decision Tree
    • Understanding Ensemble Models – Bagging and Boosting
    • Clustering Algorithms – K means clustering
    • Introduction to Deep Learning
    • A project on Artificial Neural Network
    • A Glimpse of CNN and RNN
    • Introduction to NLP
    • Complete Project on Machine Learning
    • Classification Model Building
    • Confusion Matrix
    • Precision, Recall, F1 Score, Accuracy, ROC Curve, AUC Curve and Statistics

    • Facebook – Chatbot Army
    • Twitter – Curated Timelines
    • Google – Neural Networks and ‘Machines That Dream’
    • Edgecase – Improving Ecommerce Conversion Rates
    • Baidu – The Future of Voice Search
    • HubSpot – Smarter Sales
  1. Data Visualization with R
    • Data Visualization Meaning
    • R-Line Graphs
    • R-Bar graphs
    • Histogram
    • Scatter plots
    • R-Pie charts
    • Boxplots
  2. Data Visualization with Python
    • Matplotlib: Data Visualization on Matplotlib, Bar Plot, Histogram Plot, Box Plot, Area Plot, Scatter Plot, Pie Plot
    • Seaborn: Introduction to Seaborn, Matplotlib vs Seaborn, Distribution Plot, Joint Plot, Hexagon Distribution, KDE Plot, Pair Plot, Rug Plot, Styling, Bar Plot, Count Plot, Box Plot, Violin Plot, Strip Plot, Swarm Plot, Palettes, Heatmaps, Cluster Map, Pair Grid, Facet Grid, Regression Plots
    • What are Data Operations?
    • Tour of Excel
    • Excel Worksheets
    • Excel Ribbon
    • Quick Access Toolbar
    • Keyboard Shortcuts
    • Rows & Columns
    • Transpose
    • Find and Replace (with * and Newline usage)
    • Formulas
    • Excel Functions
    • Reorder and Summarize Data
    • Sorting & Filtering
    • Pivot Tables & Charts
    • Combine Data from Multiple Sources
    • Sheet Protection
    • Print Worksheets
    • Why SQL for Data Science ?
    • Getting Started with SQL.
    • Data types in SQL
    • Basic SQL Queries + Joins
    • SQL Constraints : Concept of Keys
    • Introduction to Relational DB and Tables.
    • SQL Functions

Here is the list of projects we are doing in this CF-DORI Training + Internship.


1. Python – Student Portfolio
2. Python – Rock Paper Scissor
3. Python – Multiplication Tables Generator
4. Python – Real Calculator
5. Python – Bulk File Rename
6. NumPy & Pandas – Handling Real World Financial Data with Pandas
7. R Project still under discussion
8. Machine Learning – Music Preference Predictor
9. Machine Learning – Car Price Prediction using Regression Model
10. Machine Learning – Credit Card Defaulters prediction using ANN
11. Data Visualization – Covid Data Analysis with Matplotlib
12. SQL – Own Database Management System
13. MS Excel – Colleges Data Cleaning & Entry using MS Excel


After the training you will go through a placements prep consisting of the following modules.


1. LinkedIn Profile Building
2. Resume Building
3. GD Tips
4. Personal Interview Prep (P.I.)
5. ..Updating

Any topic of any module can be modified before the commencement of the training. Please check the final curriculum atleast 1 week prior to starting the course.


Complete program is online, there is no offline interaction.

Certificate of Internship

All interns get a "Certificate of Internship" with comments after successful completion of 60 days of internship.

Certificate of Training

All interns get a "Certificate of Training" on successful completion of the Data Science: Research and Operations Training.

Performance Certificate

A "Certificate of Distinction" will be provided to the best performers in the training and internship.

Joining Opportunity

Opportunity to be a part of College Finder is given to the best candidates and they are hired for full-time/part-time jobs at College Finder.

Video Lectures

The complete course will be through pre-recorded live streams, videos, and webinars. You will get around 50+ hours of video.

Hands-On Projects

You will get a lot of several hands-on projects on every topic. All Projects will be explained with solution.

Networking Opportunity

A multicultural and diverse working environment is available for interns, they can interact with other interns of similar interests to improve communication skills.

12+ International Trainers

You will be taught by different mentors for different topics from all over the globe, who are expert in their specific fields. You will learn by experts from Kenya, Malaysia, Yemen, India etc.

CFT Placement Prep

Dedicated Placement Preparation Course. With guidance for Resume building, Linkedln profile building, Group Discussion, Interviews, etc.

We are providing the complete training for a very low price, and we are doing this for a good cause. A lot of students from smaller towns are now able to enroll. Our only profit model here is the number of enrollments, we can only continue making new courses if we have more students joining the course.
Please share it to your connections.

Contact Us

If you have any questions concerning the internship, please reach out to us.

No boundaries on field of study or age etc. Enthusiasts interested in learning Data Science whether to change career at a later age or to start career at a young age are all welcome.

Candidates can join if they have a minimum age of 16 and can understand English well.

We will use Google Colab when high power is needed, hence there is no strict system requirements. You need good internet connectivity on any basic laptop.


Also there are no pre-requisites as we are starting the topics from basics.

There is no last date, the registrations will be ongoing always. You may miss any offers currently available.

Yes, we start from absolute basics and take you to the advanced level. The training is for beginners and moderate level students. Most of the students are beginners.

We have students from various locations, from African, European and Asian countries. All are from different time zones. So we cant make the lessons as live streams. Moreover, due to the no eligibility boundary feature, there is a diverse variety of students, some are doing jobs, some go to college etc, so all can’t be available at the same time.

You get all the sessions as recorded, which you can watch at your own time.

We have live 18/7 live support available, you can also escalate your issues to higher authority if you need a second opinion or answer to any query.


For doubts support . On lesson page in course dashboard, students have a QnA section where mentors will reply to their doubts. Moreover, in the first lesson we have shared the link to a LinkedIn group, where students can interact with each other and also discuss doubts with their mentors.

Start Instantly :

Click here go to the trainings website and get the course there.


Schedule for Later :

Click here to schedule your starting date.

You have to put 60 minutes a day for 60 days aprox.

Timings are flexible, you can study at your own time; daily around 60 minutes of content unlocks for you.

You will get assistance for placement. We will share your resume with several companies that will then call you for interviews.

The placements will range from 4lpa to 12lpa.
We also send a few opportunities to you as well, where you can apply yourself.

That’s totally fine, the course is designed to be completely flexible for all fields of study. It starts from complete beginner level.

New Year 2022


Registration Fee includes everything in this program.

Courses, Trainings, Projects, Webinars and Certificates.


We accept international applications, WhatsApp us for queries.

With 4.5 stars on Trustpilot, and plethora of happy students, we are sure you will be satisfied with the training. You get a 7 days money back guarantee* with this course, you can access the material for 7 days and if you have issues with the training, we will refund your complete course fee.

We are serious about making this training the best Data Science training at an amazingly affordable rate.

*TnC Applied : Refer This Page

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