Python for Data Analytics
About This Course
INSTRUCTOR-LED LIVE TRAINING
- 40 hours Live Sessions
- 25+ hours of offline
- Assignments for continuous learning after the course completion
- 30+ hours of Hands-on with Python
- Includes 3 Live Projects
OVERVIEW
Welcome to the course “Python for Data Analytics”. It is designed to equip you with the ability to apply knowledge and life skills of Python as a programming language and to understand how this is important in Data Analytics and Data Science space. Python is one of the most-used programming languages adopted by developers. You learn the key aspects of Python from scratch even if you don’t have any background in python programming.
COURSE OBJECTIVES
- Analyse and translate business requirements of software into multiple functions
- Write programmes and codes that are aligned with business requirements
- Draft and design overall coding frameworks as a guide for organising codes
- Select appropriate programming languages for business use cases
- Code solutions using required programming languages
- Assess written codes to identify errors and gaps to be addressed
- Test and debug codes to ensure workability
- Incorporate improvements and make corrections to programmers and codes to achieve desired outcomes
- Document programming and coding updates and changes for business and technical professionals
LEARNING OUTCOMES
We are confident that at the end of the workshop, you should be able to:
- Understand on Fundamentals of Python and apply its installation knowledge
- Understand data types and string manipulation for python along with to apply
knowledge on different Variable - Understand logic and control statements and evaluate their outcomes
- Apply programming techniques with Object Oriented Concepts with design and documentation
- Understand Dictionary, Array, List and other User defined data types along with their applications
- Understand File handling techniques and Data Extraction with database connectivity
- Apply knowledge of Exception handling techniques and evaluate efficiency of program codes
- Learning Numpy, Pandas and Python Module
- Learning Data Visualization using Python
- Working with Financial data use case. Live presentation of Financial Case study solution preparation.
Learning Objectives
Apply best practices and knowledge to think through a problem rather than try to memorise the solution.
Be able to identify many electrical and mechanical machines.
Apply engineering concepts across multiple engineering disciplines.
Target Audience
- Anyone who is keen to learn the fundamentals of data science programming.
- Aspiring Data Science Professionals
- No prior experience or background in coding is required
Curriculum
6 Lessons40h
