The Python Fundamentals course is designed to provide students with a strong foundation in the Python programming language and its applications in data science. The course covers the basics of programming in Python, including variables, data types, loops, functions, and objects. Students will learn how to work with data structures such as lists, dictionaries, and tuples, and manipulate data using libraries such as NumPy and Pandas. The course also introduces students to visualization and data analysis techniques using Matplotlib and Seaborn. By the end of the course, students will be proficient in using Python for data science tasks, including data cleaning, analysis, and visualization. This course is suitable for individuals with no prior programming experience as well as those who wish to expand their knowledge of Python for data science.
Why should you enroll into a Python course?
- Versatility: Python is a versatile language used in a wide range of industries, including data science, web development, artificial intelligence, and automation.
- High demand: There is a high demand for Python developers in the job market due to the growing demand for data-driven decision making and automation.
- Easy to learn: Python is easy to learn and use, making it an excellent choice for beginners who want to learn programming.
- Large community: Python has a large and active community of developers who contribute to its development and offer support to new learners.
- Fast prototyping: Python’s simplicity and readability make it ideal for fast prototyping and development.
- Huge library ecosystem: Python has a vast library ecosystem, including libraries for data science, machine learning, web development, and more.
- Cost-effective: Python is open-source and free, making it a cost-effective option for businesses and individuals.
- Flexibility: Python can be used on various platforms and operating systems, making it a flexible language.
- Future-proof: Python is constantly evolving, with new versions and libraries released regularly, making it future-proof.
- Career growth: Learning Python can lead to career growth and opportunities in various fields, including data science, web development, artificial intelligence, and automation.
Career Pathways, Average Salary and Hiring Companies
After undertaking a course in Python, there are various career pathways you can pursue, including:
- Python Developer: A Python developer creates web applications, software programs, and other tools using Python. They are responsible for writing clean, maintainable, and efficient code that meets the project requirements. The average salary for a Python Developer in India is around ₹4,50,000 per annum. Major hiring companies include Infosys, TCS, Wipro, IBM, Accenture, Capgemini, Cognizant, HCL, and Tech Mahindra.
- Data Analyst: A data analyst collects, processes, and performs statistical analyses on large data sets to derive insights and make informed business decisions. Python is widely used in data analysis due to its libraries such as pandas, numpy, and matplotlib. The average salary for a data analyst in India is around ₹4,00,000 per annum. Major hiring companies include Accenture, Capgemini, Cognizant, Deloitte, Ernst & Young, Infosys, KPMG, TCS, and Wipro.
- Machine Learning Engineer: A machine learning engineer develops and deploys machine learning algorithms and models that can learn from data and make predictions. Python is the most popular language used in machine learning due to its libraries such as scikit-learn, tensorflow, and keras. The average salary for a machine learning engineer in India is around ₹9,00,000 per annum. Major hiring companies include Amazon, Google, IBM, Microsoft, Nvidia, and Qualcomm.
- DevOps Engineer: A DevOps engineer is responsible for the automation of software development, testing, and deployment processes to ensure the continuous delivery of high-quality software. Python is used in DevOps for scripting, automation, and configuration management. The average salary for a DevOps engineer in India is around ₹8,50,000 per annum. Major hiring companies include Accenture, Capgemini, Cognizant, Infosys, TCS, Wipro, and Amazon.
- Full-stack Developer: A full-stack developer is responsible for developing both the front-end and back-end of web applications. Python is used in full-stack development with popular frameworks such as Django and Flask. The average salary for a full-stack developer in India is around ₹6,00,000 per annum. Major hiring companies include Accenture, Capgemini, Cognizant, Deloitte, IBM, Infosys, TCS, and Wipro.
Background/Introduction to Python: In this component, students are introduced to the basics of Python, its history, and its applications in various fields. Learning will also include the fundamental concepts of programming, such as data types, variables, and control flow.
Basic Syntax: Exploring the fundamental syntax of Python programming language. This will further cover learning about the syntax rules, indentation, comments, and whitespace.
Variable types: Lists,Tuples,Dictionaries,sets: This covers the different variable types in Python, including lists, tuples, dictionaries, and sets. This further includes learning how to create, manipulate and access data from these variables.
Basic Operators: Learning about the different types of operators in Python, including arithmetic, comparison, logical, and assignment operators. This includes how to use these operators to perform basic arithmetic operations and compare variables.
Control Flow: Exploring conditional statements, loops, and branching structures in Python. This includes learning how to use these control structures to control the flow of program execution.
Functions: In this component, students learn about functions in Python, how to create them, and how to use them. They learn about the importance of functions in modular programming and how to call them from different parts of the program.
File I/O: Learning how to read and write data to files using Python. This includes learning how to open files, read from them, write to them, and close them properly.
Exceptions: In this component, students learn about exception handling in Python. They learn how to handle errors and exceptions in their code and how to use try and except statements to handle different types of exceptions.
Classes: In this component, students learn about object-oriented programming (OOP) concepts in Python, including classes, objects, and inheritance. They learn how to create classes and objects, and how to use them in their programs.
Libraries: In this component, students learn about the various libraries available in Python for data analysis, data visualization, and scientific computing. They learn how to install and import these libraries and how to use them in their programs.
Regex: In this component, students learn about regular expressions in Python. They learn how to use regular expressions to search and manipulate text data.
Database access: Understanding how to connect to databases using Python and how to perform basic database operations such as creating tables, inserting data, and querying data. This also covers database drivers and how to use them to access databases from Python programs.