Data Science Workshop Syllabus and Delivery Plan by VigorEdTech

Workshop Overview:

This workshop is designed to introduce participants to the field of Data Science, covering essential concepts, tools, and techniques. It emphasizes hands-on learning, enabling participants to analyze data, build models, and draw insights. The program prepares learners for real-world applications in various industries such as finance, healthcare, and marketing.

Syllabus:

Module 1: Introduction to Data Science

• What is Data Science?


• The Data Science Lifecycle


• Roles and Skills of a Data Scientist


• Applications of Data Science in Industry

Module 2: Data Manipulation and Visualization

• Introduction to Data Types and Structures


• Data Manipulation with Pandas


• Data Cleaning and Preprocessing


• Data Visualization Tools and Techniques
  
  
  
  • Matplotlib
  
  
  • Seaborn
  
  
  • Plotly
  
  
  
  

Module 3: Statistics and Probability for Data Science

• Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation)


• Probability Distributions


• Hypothesis Testing


• Correlation and Regression Analysis

Module 4: Machine Learning Basics

• Introduction to Machine Learning


• Supervised Learning Algorithms:
  
  
  
  • Linear Regression
  
  
  • Logistic Regression
  
  
  • Decision Trees
  
  
  
  


• Unsupervised Learning Algorithms:
  
  
  
  • Clustering (K-Means, Hierarchical Clustering)
  
  
  • Dimensionality Reduction (PCA)
  
  
  
  

Module 5: Working with Real-World Data

• Collecting Data from APIs and Databases


• Data Wrangling Techniques


• Handling Missing Values and Outliers


• Case Study: Solving a Real-World Business Problem

Module 6: Advanced Data Science Tools

• Introduction to Big Data and Spark


• Basics of SQL for Data Extraction


• Introduction to Time Series Analysis


• Introduction to Natural Language Processing (NLP)

Module 7: Deployment and Visualization

• Building Dashboards with Power BI/Tableau


• Deploying Machine Learning Models


• Sharing Insights through Reports and Dashboards

Module 8: Ethics and Future of Data Science

• Data Privacy and Ethical Considerations


• Bias in Data and Algorithms


• Future Trends in Data Science (AI Integration, Real-Time Analytics)

Delivery Plan:

Duration:

• Total Workshop Duration: 24 Weeks


• Weekly Commitment: 6 hours (3 sessions x 2 hours each)

Mode of Delivery:

• Online (via Virtual Classroom) or In-person

Methodology:

• Interactive Sessions: Live lectures and Q&A with industry experts


• Hands-on Practice: Coding exercises and data analysis projects using Python


• Group Activities: Collaborative mini-projects and case studies


• Assessments: Weekly quizzes and a final project presentation

Resources Provided:

• Study Materials: PDFs, eBooks, and Tutorials


• Access to Jupyter Notebooks and Virtual Labs


• Recorded Sessions for Revision

Certification:

• Participants who complete the workshop and final project will receive a certificate of completion.

Additional Features:

• Mentorship: One-on-one sessions with mentors for personalized guidance


• Community Access: Join a network of data enthusiasts and professionals


• Career Support: Resume building, interview preparation, and job referrals

Target Audience:

• Students and professionals new to Data Science


• IT professionals looking to upskill in data analysis


• Entrepreneurs and business professionals aiming to leverage data for decision-making

For inquiries, visit vigoedtech.in or contact us directly.