Data Science: Operations & Research 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, learn the tools used by Data Scientists to tackle challenges and complete various life saving tasks for the company’s survival! Beginner to Expert in 60 Days. About the program. Data Science : […]

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

Beginner to Expert in 60 Days.

About the program.

Data Science : Research & Operations Training + Internship is a 60 day 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 2-4LPA package to work in a far different field from the actual Data Science. What we do then? We teach you everything a data science fresher is expected to know. We 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. 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.

MORE INFORMATION.

 

Orientation & Introduction to Data Science

1
Orientation And Info
7mins
2
LinkedIn Profile Update
1 question
3
Journey Towards Data Science
21mins

Python Programming

1
Introduction to Python
7 mins
2
Anaconda – Installation
10 mins
3
Hello World with Python
21 mins
4
Variables and Data Types in Python
75 mins
5
Project 1 : Student Portfolio
6
Strings and Lists in Python
90 mins
7
Conditional Statements in Python
68 mins
8
Project 2 : Rock Paper Scissor
27 mins
9
Iterations in Python – For and While Loop
78 mins
10
Methods & Functions
84 mins
11
Project 3 : Multiplication Tables
12
Project 4 : Real Calculator
30 mins
13
Lists, Tuples, Dictionaries
60 mins
14
How’s the course so far ?
15
Object Oriented Programming in Python
60 mins
16
Graphical User Interface with Tkinter
54 mins
17
Project 5 – News App with Tkinter : Part 1
36 mins
18
Project 5 : News App with Tkinter : Part 2
44 mins
19
Project 5 – News App with Tkinter : Part 3
38 mins
20
Project 6 : Bulk File Renamer
19 mins
21
Bulk File Renamer Error Resolving
3 mins

Batch Leader Selections

1
Batch Leader – Video Task (Optional)
2 Days

NumPy and Pandas

1
Computing with NumPy
43 mins
2
Introduction to Pandas
13 mins
3
Dataframes
20 mins
4
Reindexing & Working with Text Data
32 mins
5
Invalid Missing Data and GroupBy
30 mins
6
Merging and Concatenation
16 mins
7
Time Date Functionality & Categorical Data
21 mins
8
Project 7 – Real World Financial Data Analysis
43 mins

R Programming for Statistics & Data Science

1
Introduction, Installation and R Operators
42 mins
2
Datatypes in R
47 mins
3
Variables in R
46 mins
4
Control Flow – If Else and Loops
49 mins
5
Decision Making in R
42 mins
6
Project 8 – Simple Calculator with R
04 mins
7
Recursive and Conversion Functions
37 mins
8
Data Structures in R
51 mins
9
Object Oriented Programming – OOPs
47 mins
10
Error Handling in R
47 mins
11
Introduction to File Handling
34 mins
12
File Handling – Continued
38 mins
13
Data Interfaces
46 mins

Advanced Statistics and Probability with R

1
Statistics and Data
08 mins
2
Head First Statistics – Book by O’Reilly
717 pages
3
Measures of Central Tendency in R
18 mins
4
Measures of Dispersion in R
15 mins
5
Measure of Relationship Between Variables
11 mins
6
MAE, MSE, RMSE and R-Squared
10 mins
7
Important Commands for Descriptive Stats
22 mins
8
Inferential Statistics & Hypothesis Testing
18 mins
9
Bootstrapping
11 mins
10
ANOVA
15 mins
11
Normal Distribution
11 mins
12
Binomial Distribution
08 mins
13
Basic Probability
05 mins
14
Skewness & Kurtosis
10 mins
15
Chi-Square Test
06 mins
16
Regression
17 mins
17
Survival Analysis
12 mins

A Precursory Glance into the World of Machine Learning

1
Uses of Machine Learning
32 mins
2
Linear Regression
39 mins
3
Logistic Regression
1 hrs 05 mins

Machine Learning Essentials

1
Introduction to Machine Learning
17 mins
2
Linear Regression Model
13 mins
3
Classification Model
20 mins
4
Classification Metrics in Depth
13 mins
5
Statistics – Quick Revision
21 mins
6
Central Limit Theorem and Decision Trees
44 mins
7
Ensemble Model and Clustering
31 mins
8
Project 8 – Car Price Prediction – Part 1
56 mins
9
Project 8 – Car Price Prediction – Part 2
52 mins
10
ANN & CNN
72 mins
11
Introduction to Google Colab
07 mins
12
Project 9 – Music Preference Predictor
36 mins
13
Project 10 – Credit Card Defaulters Prediction
56 mins
14
Recurrent Neural Network – RNN
39 mins

Data Visualization with Python and R

1
Data Visualization – Introduction
12 mins
2
Basic Data Visualization in R
24 mins
3
Basic Visualization in R – Continued
32 mins
4
Advanced Data Visualization in R
22 mins
5
Data Visualization in Python – Matplotlib
56 mins
6
Data Visualization in Python – Seaborn
44 mins
7
Seaborn – Continued
63 mins
8
Project 11 – Covid Statistics Tracker
61 mins

SQL for Data Science

1
Introduction and Significance of SQL
14 mins
2
Data and SQL, MySQL Workbench Installation
16 mins
3
SQL Statements and Constraints
25 mins
4
SQL Keys, Datatypes and Case Manipulation
14 mins
5
Character Manipulation
34 mins
6
Numeric Functions
13 mins
7
SQL Joins
24 mins
8
Basic SQL Queries
12 mins
9
Python and SQL
66 mins
10
Project 12 – Corporate Assignment 1
22 mins
11
Project 12 – Corporate Assignment 2
21 mins
12
Project 12 – Corporate Assignment 3
17 mins
13
Project 12 – Corporate Assignment 4
22 mins
14
Project 12 – Corporate Assignment 5
13 mins

Final Steps

1
CF-DORI : Final Exam
41 questions
2
Placement & Certificate Form

CFT Placement Prep (To be Uploaded)

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.
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 16 and understands English well.
Yes, we start from absolute basics. The training is designed for beginners and moderate level students and hence we start each topic from beginner level.
We Provide Recorded Classes. We have students from different backgrounds some have day or night-shift jobs some have colleges so all can't sit at the same time for sessions. What we do, is we record the lessons and stream them according to the country's time (being in different timezones also is an issue, as we allow international applications). You get the sessions, files, projects, and your daily schedule, and you are free to select any time slot of the day, based on your availability, and complete the tasks. Also to cover the huge syllabus in a short time, we have to edit out the unnecessary parts like breaks, typing, etc. and add transitions for better visibility.

The following modules have been redesigned:

R Programming, Advanced Statistics, Data Visualization, Placement Prep.

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CF DORI Curriculum - Updated

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