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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

Introduction to Data Science in Python is an online certification programme provided by the University of Michigan and available on Coursera which is one of the five specializations of Data Science. Thus, this course must be pursued prior to the other course in the specialisation i.e Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python. Learners will be able to study data science in Python in greater depth with the tutelage of experienced instructors.

Introduction to Data Science in Python Certification, accessible on the platform of Coursera, will expose the candidates to basic techniques of Python programming such as lambdas, reading the CSV files, and the NumPy library and python programming environment. By enrolling in the Introduction to Data Science in Python Online Course, the learner will develop the capacity to deal with tabular data and manipulate it along with running the fundamental inferential statistical analyses.

Introduction to Data Science in Python Certification by Coursera will shed light on data manipulation, and the process of using the group by and pivot tables in an effective fashion. Introduction to Data Science in Python Certification Syllabus will help the students explore the cleaning techniques using the popular python pandas data science library and usage of the Series and DataFrame for data analysis and many more.

The Highlights

Provided by Coursera
Approximately 34 hours of programme
Offered by the University of Michigan
Flexible Deadlines
Intermediate Level Course
Shareable Certificate
Financial Aid Available
100% Online Course

Programme Offerings

English videos with multiple subtitles
intermediate level course
practice quizzes
Graded Assignments with peer feedback
graded Quizzes with feedback
Graded Programming Assignments
14 day refund period
EMI payment options

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Coursera

Introduction to Data Science in Python Certification Fee will differ based on the candidate’s learning duration in terms of the month. The free structure is provided in the table given below:

Description	Total Fee in INR
Course Fee, 1 month	Rs. 4,074
Course Fee, 3 months	Rs. 8,149
Course Fee, 6 months	Rs. 12,224

Eligibility Criteria

Certification Qualifying Details

The students are required to attend the programme in the full sense by completing all of the course materials, readings, videos, graded and peer-reviewed assignments, quizzes, etc to be eligible to be conferred with Introduction to Data Science in Python Certification.

What you will learn

Data science knowledgeKnowledge of Python

Through the Introduction to Data Science in Python Training, the learners will be able to build a solid understanding of the following concepts:

Python Programming
Numpy
Pandas
Data Cleansing

Who it is for

Data ScientistPython Programmer

Introduction to Data Science in Python Classes is the course designed as part of five specializations in data science and thus, the course is suitable for the professionals such as Python Programmers, Data scientists, etc.

Admission Details

Step 1- First, the candidates are required to register and sign up on https://www.coursera.org/ to get the courses offered on Coursera.

Step 2- After activating the Coursera account, the candidate can sign in.

Step 3- Then, the candidate can search the ‘ University of Michigan’ in the search box to be able to find the courses offered by the University of Michigan.

Step 4- Find the course ‘Introduction to Data Science in Python’ in the list and click on it.

Step 5- Then, the page of the course will appear, click on the option ‘enrol’ and pay the mentioned amount of fee or can just audit the course without paying the fee.

The Syllabus

Videos

Introduction to Specialization
Introduction to the Course
The Coursera Jupyter Notebook System
Python Functions
Python Types and Sequences
Python More on Strings
Python Demonstration: Reading and Writing CSV files
Python Dates and Times
Advanced Python Objects, map
Advanced Python Lambda and List Comprehensions
Numerical Python Library (NumPy)
Manipulating Text with Regular Expression

Readings

Syllabus
Notice for Auditing Learners: Assignment Submission
Help Us Learn More About You!
Week 1 Textbook Reading Assignment (Optional)
50 years of Data Science, David Donoho (Optional)
Syllabus
Regular Expression Operations documentation

Quiz

Quiz 1

Programming Assignment

Assignment 1

Ungraded Labs

Your Personal Jupyter Notebook Workspace
Module 1 Jupyter Notebooks

Plugin

Regex Practice Session

Videos

Introduction to Pandas
The Series Data Structure
Querying a Series
DataFrame Data Structure
DataFrame Indexing and Loading
Querying a DataFrame
Indexing Dataframes
Missing Values
Example: Manipulating DataFrame

Readings

Reading Assignments (Optional)

Quiz

Quiz 2

Programming Assignment

Assignment 2

Ungraded Labs

Module 2 Jupyter Notebooks

Videos

Merging Dataframes
Pandas Idioms
Group by
Scales
Pivot Table
Date/Time Functionality

Reading

Week 3 Reading Assignments (Optional)

Quiz

Quiz 3

Programming Assignment

Assignment 3

Ungraded Labs

Module 3 Jupyter Notebooks

Videos

Basic Statistical Testing
Other Forms of Structured Data

Readings

Science Isn't Broken: p-hacking
Goodhart's Law (Optional)
The 5 Graph Algorithms that you should know
Post-course Survey
Keep Learning with Michigan Online!

Quiz

Final Quiz

Programming Assignment

Assignment 4

Ungraded Labs

Module 4 Jupyter Notebooks

Instructors

UM–Ann Arbor Frequently Asked Questions (FAQ's)

1: Who instructs the Introduction to Data Science in Python Online Certification?

The programme is instructed by Christopher Brooks who is the Assistant Professor in the School of Information.

2: How much time does the learner need to complete the Introduction to Data Science in Python Online Course?

The learners can complete the programme approximately within 34 hours.

3: Is the complete process of the programme in the online mode?

Yes, the full process of the course is in the online mode and thus, the students can learn on their own schedule.

4: Does Coursera provide the subtitles for the videos?

Coursera provides multiple subtitles for the course videos in numerous languages of Arabic, French, Portuguese (European), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, English, and Spanish.

5: Does Coursera render placement support after the programme?

No, the students will not be rendered placement support after the course.