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Become a Python Certified Professional with our Python Course in just 2 months!
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This Python course provides a thorough introduction to Python, a high-level, general-purpose dynamic programming language. The course covers data analysis, scientific computing, data visualization, web scraping, database interface, and essential programming principles such as object-oriented design and multithreading.
| Criteria | C++ | Java | Python |
| Ease of Use | Verbose | Verbose | Simpler and dynamically typed |
| Scalability | Platform-depended | Cross-platform | Cross-platform |
| Deployment | Android and web application | Big Data | Data Science and Machine Learning |
| Average Salary | US$78,368 | US$87,424 | US$103,492 |
This course will teach you fundamental and advanced Python concepts such as object-oriented programming (OOP), expressions, data types, control flow (looping and conditionals), functions, classes, Python standard libraries, exception handling, multithreading, modules and packages, database connectivity, web scraping with BeautifulSoup, and essential libraries for data analysis and scientific computing such as NumPy, SciPy, Pandas, and Matplotlib.
There are no prerequisites for this course. It is intended for beginners and covers all of the fundamentals of Python from the very beginning level. However, having a fundamental knowledge of programming ideas or prior experience with any programming language could prove helpful and may help you adopt the content faster.
Python programming is used in the backend, and it is one of the top languages for beginners to learn and implement. It is very similar to Ruby. However, it requires comparatively less effort to code. This language is easily approachable, and you are not required to know or have skills in any other programming language to learn it.
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Data Analyst | Capgemini
Thanks to Intellipaat’s comprehensive Data Analyst course and dedicated support, I secured my first job at Capgemini as a fresher. The industry-relevant curriculum and constant guidance made my career dream a reality!
Fresher
Data Analyst
Junior Software Engineer | Cognizant
Completed Intellipaat’s data science course with Python and gained practical, hands-on experience. The training was well-structured with excellent instructors and valuable job support.
Program Analyst Trainee
Junior Software Engineer
Senior Associate | Axtria
Joining the Python course helped me become a Python developer. After enrolling, I consistently worked on improving my skills and was able to successfully upskill myself.
Software Engineer
Senior Associate
57% Average Salary Hike
45 LPA Highest Salary
12000+ Career Transitions
300+ Hiring Partners
Career Transition Handbook
*Past record is no guarantee of future job prospects
Rishab is a data science & AI expert with 10 years of experience, specializing in Python for demand planning, forecasting, and MLOps. Skilled in leveraging Python to deliver data-driven solutions for Fortune 500 clients.
Ankit is a data scientist with 10 years of experience delivering data-driven solutions using Python for Fortune 500 companies. Expertise in predictive analytics, machine learning, and data visualization with tools like Python, Tableau, and Power BI.
Vamsi is a data analyst with 9 years of experience in Python, machine learning, and AI. Awarded the 2023 Graham Bell Award for excellence in data science. Expert in deploying scalable models and driving insights using Python.
Sahil Mattoo is a senior consultant in analytics & data science at Eli Lilly and Company, bringing over 17 years of experience in program, project, and product management. He is an expert in Python, leading projects for AT&T, Manheim, and DirecTV.
Python Basic Constructs
Exception Handling
Matplotlib
OOPS in Python
Multi-threading
Python for Apache Spark
Pandas NumPy & SciPy
Web Scraping
Packages & Functions
Database Connections
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1.1 Introduction to Python Language
1.2 Features and the advantages of Python over other programming languages
1.3 Python installation – Windows, Mac and Linux distribution for Anaconda Python
1.4 Deploying Python IDE
1.5 Basic Python commands, data types, variables, keywords and more
Hands-on Exercise – Installing Python Anaconda for Windows, Linux, and Mac.
2.1 Built-in data types in Python
2.2 Learn classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug
2.3 Basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise
2.4 Loop and control statements while, for, if, break, else, continue.
Hands-on Exercise –
1. Write your first Python program
2. Write a Python Function (with and without parameters)
3. Use Lambda expression
4. Write a class
5. Create a member function and a variable
6. Create an object
7. Write a for loop
3.1 How to write OOP concepts program in Python
3.2 Connecting to a database
3.3 Classes and objects in Python
3.4 OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation
3.5 Python functions, return types and parameters
3.6 Lambda expressions
Hands-on Exercise –
1. Creating an application that helps to check balances, deposit money, and withdraw money using the concepts of OOPs
4.1 Understanding the database, need for database
4.2 Installing MySQL on Windows
4.3 Understanding database connections using Python
Hands-on Exercise – Demo on database connection using Python and pulling the data.
5.1 Introduction to arrays and matrices
5.2 Broadcasting of array math, indexing of array
5.3 Standard deviation, conditional probability, correlation and covariance.
Hands-on Exercise –
1. How to import the NumPy module?
2. Creating an array using ND-array
3. Calculating standard deviation on an array of numbers
4. Calculating the correlation between two variables
6.1 Introduction to SciPy
6.2 Functions building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, and SciPy with Bayes’ Theorem
Hands-on Exercise –
1. Importing of SciPy
2. Applying Bayes’ theorem to the given dataset
7.1 How to plot graphs and charts with Python?
7.2 Various aspects of line, scatter, bar, histogram, 3D, the API of Matplotlib, and subplots
Hands-on Exercise –
1. Deploying Matplotlib for creating Pie, Scatter, Line, and Histogram
8.1 Introduction to Python dataframes
8.2 Importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe
8.3 Various data operations like selecting, filtering, sorting, viewing, joining, combining
Hands-on Exercise –
1. Working on importing data from JSON files
2. Selecting record by a group
3. Applying filter on top, viewing records
9.1 Introduction to Exception Handling
9.2 Scenarios in Exception Handling with its execution
9.3 Arithmetic exception
9.4 RAISE of Exception
9.5 What is Random List, running a Random list on Jupyter Notebook
9.6 Value Error in Exception Handling.
Hands-on Exercise –
1. Demo on Exception Handling with an Industry-Based Use Case
10.1 Introduction to Thread, the need of threads
10.2 What are thread functions?
10.3 Performing various operations on thread like joining a thread, starting a thread, and enumeration in a thread
10.4 Creating a Multithread, finishing the multithreads.
10.5 Understanding race condition, lock, and synchronization
Hands-on Exercise –
1. Demo on Starting a Thread and a Multithread and then performing multiple operations on them
11.1 Introduction to modules in Python, the need for modules
11.2 How to import modules in Python
11.3 Locating a module, namespace, and scoping
11.4 Arithmetic operations on Modules using a function
11.5 Introduction to the search path, global and local functions, filter functions
11.6 Python packages, import in packages, various ways of accessing the packages
11.7 Decorators, pointer assignments, and Xldr
Hands-on Exercise –
1. Demo on Importing the modules and performing various operations on them using arithmetic functions
2. Importing various packages, accessing them, and then performing different operations on them
12.1 Introduction to web scraping in Python
12.2 Installing beautiful soup
12.3 Installing Python parser lxml
12.4 Various web scraping libraries, beautiful soup, scrapy Python packages
12.5 Creating soup object with input HTML
12.6 Searching of tree, full or partial parsing, output print
Hands-on Exercise –
1. Installation of beautiful soup and lxml Python parser
2. Making a soup object with input HTML file
3. Navigating using Py objects in the soup tree
Python Projects
Proud to have completed the Python Course from Intellipaat, which strengthened my programming skills and laid a strong foundation in data science. This achievement marks a key step in my career transition into the IT and analytics domain.
Land Your Dream Job Like Our Alumni
There are numerous job opportunities available for both entry-level and experienced professionals who have gained skills in the Python programming language after completing the course with us. Some of the job roles that you will become eligible to apply for are as follows:
Intellipaat offers courses on big data hadoop, data scientist course, machine learning, artificial intelligence, Python for Data Science, data analyst course, business analytics certification
If you are looking for free resources on Python then read our blogs on Python tutorial, and Python interview questions.
Yes. At Intellipaat, we offer one practice test that is designed keeping in mind the current market demands and the syllabus of the actual examination. This practice test aims to prepare you for the same by giving you an idea of the type of questions and the format.
Intellipaat offers both live online Python Course training and self-paced courses. Live online training includes live lectures by industry experts, while self-paced courses only provide pre-recorded video lectures.
Major organizations that are hiring Python-certified developers and other professionals skilled in Python programming language are mentioned below:
You can enroll in this best course offered by Intellipaat by choosing the batch that is convenient to you and making the payment for it.
Three technical 1:1 sessions per month will be allowed.
Yes, as per our refund policy, once the enrollment is done no refund is applicable.