Data Science and Python Automation

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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

 

    • 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
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