Total Duration: 30 hours

Average Lecture Segment: 10 minutes per lecture

Weekly Segment: 4 hours

Credits: 6 (1 credit = 5 hours)

Course Fee Details

Early Bird Registration Fee by February 15, 2025: ₹ 250

February 16, 2025 to February 30, 2025: ₹ 500

Standard Registration Fee: ₹1000

Impotant Dates

• Course Start Date: 20 February 2025
• Completion Date: 25 April 2025

Course Overview:

“Data Analytics with Python: Foundations and Applications” is a comprehensive course designed to introduce participants to the fundamentals of data analysis using Python. It covers essential topics such as Python programming, data wrangling with pandas, data visualization with Matplotlib and Seaborn, statistical analysis, and basic machine learning techniques. Participants will gain hands-on experience through practical assignments and a real-world project in areas like Health, Business, Social Media, Finance, and more. This course is ideal for students, professionals, and anyone looking to harness the power of data science to drive decisions and innovations.

Course Objectives:

• Understand the basics of Python programming. 

• Learn to manipulate and analyze data using Python libraries. 

• Apply statistical methods to data analysis. 

• Visualize data using Python. 

• Gain hands-on experience through projects in health science, environmental science, business analytics, social science, and medical science.

Eligibility for Enrollment:

• Undergraduate students currently enrolled in any academic program. 
• Professionals seeking to enhance their data analysis skills using Python. 

• Individuals with a basic understanding of programming and a keen interest in data science. 

• Students from health science, environmental science, and related fields are looking to apply data analysis techniques in their studies and research. 

• Anyone interested in learning the fundamentals and applications of data analysis with Python 

Course Commitment

Spend 4 hours per week on recorded lectures, assignments, quizzes, reading materials, and projects to complete the course in 10 weeks.

Prerequisites:

To ensure that students can successfully complete the course, the following prerequisites are recommended: 

• Basic Computer Literacy: Familiarity with operating systems (Windows, macOS, or Linux). Basic knowledge of file management and using web browsers 

• Mathematics Fundamentals: Understanding of basic algebra, Familiarity with basic statistics concepts (mean, median, mode, standard deviation, probability) 

• Programming Knowledge: Basic understanding of programming concepts such as variables, loops, and conditionals. Prior experience with any programming language (e.g., C, C++, Java) is beneficial but not mandatory 

• Software Installation: Ability to install software on a computer, including Python and relevant libraries (instructions will be provided during the course) 

Course Experts: Our Data Analysis with Python certificate course is led by a team of distinguished experts in the field, ensuring a comprehensive and enriching learning experience:

• Dr. Mehar Chand: Department of Mathematics, Baba Farid College, Bathinda, INDIA
• Prof.(Dr.) Pooja: Professor & Associate Dean, Sharda University, UZBEKISTAN
• Dr. Aparna Kumar: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat INDIA
• Dr. Upinder Kaur: Department of Computer Science and Engineering, Akal University, Bathinda, INDIA
• Dr. Parijata Majumdar: Department of Computer Science and Engineering, Techno College of Engineering, Agartala, Tripura, INDIA

Terms and Conditions:

• Enforce sequential learning path: Course items can only be accessed in the sequential order. Learners need to mark course items as completed to move to next item. In an already published course, all previously completed items will remain accessible.
• Enforce complete video viewing: Learners need to watch at-least 90% of the video lesson to move to next course item. It only works if sequential learning path is enabled. This feature is compatible only with videos uploaded on the platform.
• Once the registration fee is paid, it is non-refundable under any circumstances.
• The non-refundable fee ensures that participants commit to the course and helps cover the costs associated with course materials, instructor time, and administrative expenses.
• The discounted fee is applicable only for registrations completed by 31 August 2024.
• No refunds will be issued after the course start date.
• Participants must complete all assignments, quizzes, and the final project to be eligible for certification.
• Course materials are provided for personal use only and must not be shared or distributed.
• The course schedule is subject to change, with prior notice provided to all participants.
• Participants are expected to adhere to academic integrity and avoid any form of plagiarism.
• The course provider reserves the right to discontinue access to the course for violations of these terms.
• Certification is awarded based on the successful completion of all course requirements and assessments.