Duration 5 days -35 hrs.
Overview
Welcome to our comprehensive Data Science and Python Automation Training course. This program is designed to equip participants with a powerful skill set in both data science and automation using the versatile Python programming language.
Objectives
- Develop proficiency in using Flutter and Dart for Android app development.
- Create user-friendly and visually appealing interfaces following design principles.
- Build fully functional Android applications using Flutter’s capabilities.
- Learn effective testing and debugging techniques for app reliability.
- Understand the process of deploying and publishing apps to the Google Play Store.
- Explore and implement advanced features for customized user experiences.
- Apply learned skills in a comprehensive capstone project demonstrating app development capabilities.
Audience
- Data Analysts: Professionals responsible for interpreting data and extracting insights for decision-making.
- Python Developers: Individuals proficient in Python interested in leveraging the language for data analysis and automation.
- Business Intelligence Analysts: Those seeking to enhance data analysis and automation skills for business intelligence purposes.
- Data Engineers: Professionals involved in handling large datasets and interested in data analysis and automation techniques.
- Machine Learning Enthusiasts: Individuals looking to apply Python for machine learning and data automation processes.
- IT Professionals: Those aiming to enhance data-related skills and explore Python’s potential for automation in IT operations.
- Database Managers: Professionals overseeing database operations interested in leveraging Python for automation.
- Project Managers: Those overseeing projects involving data analysis, keen on enhancing outcomes through automation.
- Recent Graduates: Individuals with a background in data-related fields looking to start a career in data analysis and automation.
- Professionals in Transition: Individuals seeking to switch careers or roles and delve into the fields of data science and automation.
Pre- requisites
- Basic computer literacy
- Familiarity with programming concepts is beneficial but not required
- Basic understanding of mathematics and statistics
- No prior experience in Data Science or Python required
Course Content
Introduction to Python
- Introduction to Data Science and Its Applications
- Introduction to Python and its Versatility
- Setting Up Python Environment
- Python using Jupyter Notebook
- Python Basics: Variables, Data Types and Structures, and Operators
- Python Programming fundamentals: conditions and branching, loops, functions, exception handling, objects and classes
Data Science Libraries in Python
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- Data Wrangling with Pandas
- Basic Data Analysis with Pandas
- Using NumPy library: Arrays, One-dimensional and two-dimensional arrays, Subsetting
Numpy arrays
- Numpy: Basic Mathematical Operations and Statistics
- Data visualization using Matplotlib and Seaborn
Predictive Modelling
- Introduction to Predictive Modelling
- Introduction to Machine Learning with Python
- Scikit-Learn for Machine Learning
- Supervised Learning (Regression and Classification)
- Model Evaluation and Validation
APIs and Webscraping
- Simple and REST APIs
- HTTP Requests
- etrieving Data from Web APIs
- Data Manipulation using different file types (CSV, JSON, XML, XLXS)
- Introduction to Webscraping
Data Science Automation and Integration
- Automating Data Processing and Analysis
- Integrating Data Science Models into Automation
- Case Study on Business Forecasting and Report Automation with Python
- Automating Data Dashboard with Excel and Python
Capstone Project
- Overview of the Capstone Project
- Initial Project Planning
- Capstone Project Presentations
- Feedback and Evaluation
- Course Conclusion
