Business Internship Program

Learning business courses can provide numerous benefits and open up various opportunities. It's essential to choose courses that align with your interests and aspirations to maximise the value you gain from your education.



Month-1


Week-1

  • Introduction to Business Analytics
  • Understanding Applications of Business Analytics

Week-2

  • Understanding the role of business analytics in decision-making
  • Key concepts and terminology in business analytics

Week-3

  • Understanding Methods for data collection (Survey and Interview Techniques)
  • Understanding Methods for data collection (Web Scraping and Data Acquisition)

Week-4

  • Data cleaning and preprocessing techniques
  • Dealing with missing data and outliers

Month-2


Week-1

  • Fundamentals of EDA
  • EDA Techniques and Tools like Matplotlib and Seaborn

Week-2

  • Data Visualization Techniques
  • Extracting Insights and identifying patterns from data

Week-3

  • Understanding Descriptive Statistics like (mean, median, mode, standard deviation, etc.)
  • Descriptive Statistics Applications to describe central tendency, variability, and distribution of data

Week-4

  • Probability Theory Basics (discrete and continuous distributions)
  • Probability Distributions in Business Analytics

Month-3


Week-1

  • Basics of Hypothesis Testing
  • Other Hypothesis Testing Methods (t-tests, chi-square tests, etc.)

Week-2

  • Understanding confidence intervals and p-values
  • Practical applications of inferential statistics in business analytics

Week-3

  • Fundamentals of Predictive Modeling
  • Understanding Linear Regression Analysis

Week-4

  • Understanding Logistic Regression Analysis
  • Model Evaluation and Validation Techniques

Month-4


Week-1

  • Understanding Time Series Data
  • Understanding Time Series Data Preprocessing

Week-2

  • Applications of time series analysis in business forecasting
  • Overview of ARIMA Modeling (Autoregressive Integrated Moving Average) models for time series forecasting

Week-3

  • Introduction to Machine Learning for Business Analytics
  • Common Machine Learning Algorithms

Week-4

  • Model Building and Evaluation
  • Feature Selection and Engineering

Month-5


Week-1

  • Understanding Big Data
  • Big Data Technologies (Hadoop, Spark, etc.)

Week-2

  • Data Handling Techniques in Big Data
  • Analyzing Large Datasets with Distributed Computing

Week-3

  • Understanding Fundamentals of Optimization
  • Linear Programming (LP) and its applications

Week-4

  • Intoduction to Integer Programming (IP) and its extensions
  • Applications of Optimization in Business Decision-Making

Month-6


Week-1

  • Intoduction to Advanced Visualization Concepts
  • Understanding Tools for Advanced Data Visualization like Tableau or Power BI

Week-2

  • Understanding Dashboard Design Principles
  • Creating Interactive Dashboards

Week-3

  • Application of Business Analytics Concepts (Data collection, preprocessing, analysis)
  • Project Implementation (Developing a project plan and timeline)

Week-4

  • Presentation Preparation (Crafting an engaging and informative presentation)
  • Presentation and Reflection (Presenting the final project to mentors, peers, and stakeholders)