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Admission deadline: (Batch 30)
2024-12-01

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Batch 30 Courses

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Applied Machine Learning
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LLM & Prompt Engineering
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Business Analytics
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Microsoft SQL Server Database Management and Administration
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Introduction to Python
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Course Detail:

Course Title: Business Analytics

Introduction

The Business Analytics course at the Bangladesh-Korea Information Access Center (BK-IAC) is designed for professionals looking to enhance their skills in utilizing data for strategic decision-making in the business world. This comprehensive course covers various aspects of business analytics, from Python fundamentals to advanced machine learning model development and real-world case studies.

Objectives

To master Python fundamentals for data analysis, including variables, loops, arrays, functions, strings, and file handling.
To provide a comprehensive understanding of data handling, preprocessing, and wrangling techniques.
To delve into exploratory data analysis (EDA) and visualization using Python libraries like Matplotlib and Seaborn.
To introduce hypothesis testing and regression analysis for making informed business decisions.
To apply analytics skills through case studies in stock analysis, investment study, and other real-world scenarios.

Prerequisite

We expect participants to have prior programming knowledge, specifically in Python. If you lack this background, please learn the basics of Python before starting this course. This course does not cover Python fundamentals, and enrolling without adequate Python knowledge may lead to significant difficulties in understanding the content, resulting in a poor learning experience. This responsibility lies solely with the participant. We have also offered an "Introduction to Python" course (Course Details Link), which you can complete prior to enrolling in this course.

Tentative Class Schedule

The course length will be 8 weeks with two classes in each week and 3 hours in each class. The tentative lecture plan of the course is as follows:

Class#	Content
1	Python Environment setup, Python Fundamentals for Data Analysis (Numpy, Pandas)
2	Python Fundamentals for Data Analysis (Numpy, Pandas)
3	Data Handling - Loading, Preprocessing, and Wrangling
4	Python Advanced for Data Analysis - Matplotlib, Seaborn
5	Exploratory Data Analysis, EDA - I Descriptive Statistics, GroupBy, Correlation Study
6	Data Visualization and EDA - II Histogram, Box Plot, KDE Plot, Violin Plot, Pairplot, Bar Plot, Pie Chart Assignment 1 on Data Analysis (Preprocessing, EDA, Visualization)
7	Hypothesis Testing - 17 statistical tests for formulating, testing, and validating hypothesis (using Python)
8	Evaluation of Assignment 1
9	Single Variable Linear Regression and Multiple Regression
10	Trends and Seasonality Analysis, Time Series Analysis (ARIMA, RNN) Assignment 2 on Hypothesis Testing and Regression Analysis
11	Machine Learning model development and evaluation using Scikit-Learn
12	Case Study 1 - Stock Analysis
13	Case Study 2 - Investment Study (Risk and Return)
14	Evaluation of Assignment 2
15	Excel Blitz - Analyzing business data in Excel
16	Final Exam

Learning and Evaluation Method

Classes will be conducted in a multimedia-equipped environment.
Expert faculty members from the field of Business Analytics will lead each class.
All instructors are faculty members from the Department of CSE, BUET.
Participants will have access to PCs for practical exercises, ensuring an interactive learning experience.
Evaluation will take place through assignments and case-study.
We will provide a certificate upon successfully passing this course.

Further Query

Email: iac@cse.buet.ac.bd
Phone: 9665650-80 Ext-6438
Mobile: 01552 015596