Python Programming
Abstract of the Course.
This course introduces beginners to Python programming, covering fundamentals like data types, lists, dictionaries, conditions, loops, and functions. Students will learn error handling and input/output operations, gaining hands-on experience with data manipulation and visualization. By the end, participants will have a strong foundation in Python, preparing them to tackle various coding projects and challenges.
Course Outline
The Introduction to Python module serves as the foundation for programming and data analysis, covering essential concepts such as data types, collections, string operations, control flow, and functions. Students will learn to manipulate various data types, including integers, floats, lists, dictionaries, and arrays. The module also emphasizes control flow through conditional statements and loops, alongside defining both inbuilt and user-defined functions. Practical applications are a key focus, with sessions dedicated to input/output operations for reading and writing files, as well as working with Excel and databases. Error handling techniques will be introduced to manage exceptions effectively. Finally, students will explore data analysis using the Pandas library, enabling them to manipulate datasets and create basic visualizations, thus equipping them with the skills necessary for further exploration in data science.
Course Curriculum
- Overview of Python: History, features, and use cases.
- Setting up Python: Installing Python, IDEs (Jupyter Notebook, Anaconda).
- Writing your first Python program.
- Variables, keywords, and data types.
- Arithmetic, relational, and logical operators.
- Understanding Python syntax and indentation.
- Data Types: Integers, floats, strings, and booleans.
- Lists: Creating, slicing, and operations.
- Dictionaries: Keys, values, and dictionary methods.
- Arrays: Using NumPy for array operations.
- String Operations: Manipulating strings using methods like slicing, concatenation, and formatting.
- Conditional Statements: if, elif, and else.
- Loops: for, while, and break/continue statements.
- Iterating through data structures like lists and dictionaries.
- IO Operations
- Excel Operations
- Database Operations
- Understanding errors and exceptions.
- Using try, except, finally, and else for handling errors.
- Overview of data analysis and its importance.
- Understanding structured vs. unstructured data.
- Pandas: Reading and writing data, cleaning, filtering, and grouping data.
- Visualization: Creating charts and graphs using Matplotlib and Seaborn.
- Overview of statistics in data analysis.
- Basic concepts: Mean, median, mode, variance, and standard deviation.
- Probability basics: Random experiments, events, and probabilities.
- Types of distributions: Normal, binomial, Poisson, etc.
- Central limit Theorem
- Hypothesis Testing
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Learning outcomes
Python programming fundamentals, working with various data types and structures, controlling program flow using conditions and loops, defining and using functions, file handling (reading and writing files), error management using try-except blocks, using Pandas for data manipulation, creating basic visualizations with Pandas, performing data analysis, working with Excel and databases, understanding basic concepts of data science, debugging and troubleshooting Python code, handling exceptions effectively, implementing best practices in Python coding.
Python Decorators
Implement a Python decorator that should take whatever the decorated function returns, and writes it to a file in a new line.
Manage the Password
Develop a new version of a password manager that can keep track of all the passwords that have been set for the respective accounts.
Patient Management Application
Write an application in Django for a hospital receptionist that has features, including checking if the patient is already registered. If not register the patient.
Job Roles
According to Emergen Research, the global python market is expected to reach USD 100.6 million in 2030 and register a revenue CAGR of 44.8% during the forecast period. Python is used by over 27 million developers worldwide, according to the 2024 Stack Overflow Developer Survey.
Python Developer
Data Analyst, Data Science Intern
Python Programmer
Business Analyst
Data Analyst
Automation Engineer
Entry-Level Data Scientist
Data Engineer
Skills & Tools Covered
Why Join this Program
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Learn From Industry Experts
Engage with industry experts, benefit from their years of accumulated knowledge & experience. Enhance your capabilities in a way that textbooks and conventional learning methods might not fully capture.
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Learn & Earn Certificates
Enhance your resume, validate your competence & commitment making you a more attractive candidate to potential employers and increasing your chances of career advancement.
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Learn & Adapt
Curriculum that aligns with industry needs and standards, preparing students with the skills they need to succeed in the professional world.
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Learn Anywhere, Anytime
Offers every individual the freedom and flexibility to pursue learning on their terms. It enables access to quality content, upskill, and accommodate diverse learning styles and preferences without the limitations of time and place.
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Learn Through Project & Case Studies
Enables learners to apply theoretical knowledge, develop practical skills, and navigate real-world complexities.
Python Exam & Certification
To obtain the Python certification, you must
- Complete 85% of the online self-learning course or attend 1 complete batch of this training
- Successful evaluation of the project
Hemanth Chakka