Introduction to Data Science with Python

The GovTech Agency under the Royal Government of Bhutan brings you an exciting opportunity to enroll yourself in the Artificial Intelligence foundation learning program. Please find the necessary information and the registration link below. We hope to see you there !!!

Foundational courses cater to diverse backgrounds. It aimed to equip learners with comprehensive understanding through theoretical knowledge acquisition. This course provides a solid foundation in data science using Python, covering essential topics such as statistics, Python programming, data collection, exploratory data analysis, machine learning, natural language processing, and building interactive web applications with Streamlit. This course is designed for beginners with diverse backgrounds who are interested in learning data science and machine learning concepts using Python.

• Gain proficiency in Python programming language for data science applications.
• Understand fundamental statistical concepts necessary for machine learning.
• Learn to collect and preprocess data from various sources using Beautiful Soup.
• Perform exploratory data analysis and feature engineering to gain insights from data.
• Master basic Python libraries for data manipulation and visualization.
• Explore machine learning algorithms and techniques for predictive modeling.
• Learn natural language processing techniques for text data analysis.
• Build interactive web applications for data visualization and model deployment using Streamlit.

There are no specific knowledge prerequisites for this course; it is designed for beginners with little to no prior programming/ technical experience but a basic understanding of programming concepts (e.g., variables, loops, conditionals) would be beneficial.

Sr. No	Modules	Topic	Duration
1.	Basic Module	Introduction to Statistics for Machine Learning	4 hrs
2.	Basic Module	Introduction to Python Programming Language	4 hrs
3.	Basic Module	Collecting publicly accessible data using Beautiful Soup	2 hrs
4.	Basic Module	Basic Python Libraries for Data Science Applications	4 hrs
5.	Basic Module	EDA: Exploratory Data Analysis and Feature Engineering	4 hrs
6.	Advance Module	Data Visualization	4 hrs
7.	Advance Module	Introduction to Machine Learning	4 hrs
8.	Advance Module	Natural Language Processing	4 hrs
9.	Advance Module	Streamlit Application	2 hrs
10.	Advance Module	Project: Tourist Activity Prediction for Bhutan Tourism	4hrs

 

Attendance

• 75% of attendance

• Note: The learners of the course must attend 75% of live sessions to qualify for the course certificate.

Evaluation/ Submission of Assessments

The following are the evaluation criteria for the

• Learning checks during the live session

• Performance in weekly assignments and learning checks

• On-time submission of assignments/project activities

• Note: To qualify for the certificate it is mandatory to pass the assessment with 60% of the grade

Revoking/Removal:

In the following cases, learners will be removed from the course

• Two weeks of consecutive absences from the live session without any prior notice

• Poor performance in assignments and quizzes

• Late submission of assignments