Fundamentals of Python Programming [Python for Data Analytics]


About This Course


As one of the world’s top programming languages, Python is growing in popularity year-after-year. Python is not only easy to use, but also incredibly versatile and productive. In turn, programmers who are proficient with Python are highly desirable within leading businesses throughout Singapore and beyond.

At Laure’s Academy, we fully recognize the importance of Python, specifically in a data analysis role. That is why we developed our course, Fundamentals of Python Programming [Python for Data Analytics].

Our course uses a ground-up approach to learning, teaching beginner-friendly lessons that require no previous Python experience.

Developed by leading programmers and data science professionals, this course teaches actionable lessons including:

          Aligning code to organizational and business requirements

          Using data visualization within Python

          Transforming raw values from data sets into useful information

          And much more 


Python for Data Analytics introduces you to Python as the go-to tool for data analysis. This course takes you from fundamental to advanced topics in Python that is required by a data analyst to explore hidden insights from the data. This program is designed for learners who have little or no knowledge in any programing language. 


Python – Open source, highly flexible language comes with large number of libraries and easy-to-learn. Python for Data Science course prepares you with Python Programming capabilities for Data Manipulation, Exploratory Data Analysis and Data Visualization which are an absolute must for being a Data Analytics expert. 


  • Understanding why Python as a tool for data analytics
  • Understand Python distribution & installation
  • Understand variables, data types and data type conversion
  • Learn conditional statements, nested conditional statements
  • Learn different kind of loops
  • Understand object-oriented programming system (OOPS) concepts & design
  • Learn how to write user defined and lambda functions
  • Learn about strings & string manipulations
  • Learn about other data structures like lists, tuples, dictionaries & sets
  • Learn about various methods of lists, tuples, dictionaries & sets
  • Understand connections to other database softwares like MySQL
  • Learn about NumPy arrays and array methods
  • Learn about Pandas series object
  • Learn about Pandas dataframe object
  • Learn advanced Pandas dataframe manipulations
  • Learn data visualization using Matplotlib & Seaborn
  • Financial case study: Exploratory data analysis on financial data using Pandas dataframe and data visualization

    Who Should Attend 

  • 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

     Why Learn from US

  • Lessons to improve your programming aptitude with Python
  • Vetted content by top programmers and developers
  • Beginner-friendly lessons that require no previous experience
  • Interactive sessions complete with offline post-course assignments
  • Relevant information through real-world case studies
  • Course certificate to boost your marketability  
Module 1: Introduction to Python & Installation


Module 2: Python Data Types & Variables


Module 3:Operators & Control Statement


Module 4: String Manipulation


Module 5: List &Tuple


Module 6: Dictionary & Sets
Accordion Content
Module 7: Functional programming & OOPS Concept


Module 8: File handling
Accordion Content
Module 9: Exception handling, Regular Expression
Accordion Content
Module 10: Data Extraction
Accordion Content
Module 11: Python Numpy
Accordion Content
Module 12: Python Pandas
Accordion Content
Module 13: Data Visualization using Python
Accordion Content
Final Assessment – Case study

Accordion Content.

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
Data Science


Duration 40 hours
21 lectures
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