Learn from Home Offer

Learn from Home Offer
This Python Training Certification includes 40 courses, 13 Projects with 215+ hours of video tutorials and Lifetime access.
You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of the courses. This Python course is a package of Python related fundamentals, core and advanced concepts of several Python concepts and developing standalone or web applications using Python whether it is scripting or programming a requirement.
Python Programming
Linux System Administration with Python
Django Unchained with Python
Project on Python - Instant Markup
Project on Python Django MySQL - Creating a Blog
Course | No. of Hours | |
---|---|---|
Python for Beginners: 2022 | 3h 22m | |
Python Intermediate Training: 2022 | 3h 34m | |
Python Advanced Training: 2022 | 2h 13m | |
Data Science with Python Training 2022 | 11h 18m | |
Python Programming - 01 | 4h 33m | |
Python Programming - 02 | 3h 06m | |
Python Programming - 03 | 5h 28m | |
Python Programming - 04 | 3h 8m | |
Python Programming - 05 | 4h 22m | |
Python Programming - 06 | 3h 31m | |
Linux System Administration with Python | 13h 9m | |
Python Django | 8h 26m | |
Python Case Study - Instant Markup | 3h 28m | |
Python Django MySQL Case Study - Creating a Blog | 48m | |
Python GUI Programming using Tkinter and Python | 4h 34m | |
Python 3.5 Training | 2h 25m | |
Python Bootcamp | 10h 33m | |
Advanced Python for Data analysis | 6h 28m | |
Python Pyramid - Beginners | 6h 04m | |
Python Pyramid - Advanced | 6h 02m | |
Jupyter-IPython Notebook Training - Beginners | 6h 05m | |
Jupyter-IPython Notebook Training - Advanced | 7h 53m | |
Violent Python | 2h 39m | |
Python Case Study - Cryptography | 5h 11m | |
Matplotlib for Python Developers - Beginners | 4h 12m | |
Matplotlib for Python Developers - Intermediate | 2h 52m | |
Matplotlib for Python Developers - Advanced | 6h 37m | |
Pandas with Python Tutorial | 5h 47m | |
NumPy and Pandas Python | 5h 01m | |
Pandas Python Case Study - Data Management for Retail Dataset | 3h 28m | |
Seaborn Python - Beginners | 2h 28m | |
Seaborn Python - Intermediate | 1h 18m | |
Seaborn Python - Advanced | 1h 56m | |
PySpark Python - Beginners | 2h 3m | |
PySpark Python - Intermediate | 2h 05m | |
PySpark Python - Advanced | 1h 14m | |
Machine Learning with SciKit-Learn in Python | 8h 37m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Machine Learning using Python | 3h 26m | |
Data Science with Python | 4h 14m | |
AI Artificial Intelligence with Python | 6h 15m | |
Video Analytics using OpenCV and Python Shells | 2h 13m | |
Statistics Essentials with Python | 3h 23m | |
Project on Tensorflow - Implementing Linear Model with Python | 1h 46m | |
Project - Data Analytics with Data Exploration Case Study | 5h 7m | |
Project on ML - Random Forest Algorithm | 1h 29m | |
Python Case Study - Sentiment Analysis | 1h 06m | |
Python for Finance | 1h 7m | |
Financial Analytics with Python | 1h 6m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Time Series Analysis in Python - Sales Forecasting | 2h 12m | |
Machine Learning Python Case Study - Diabetes Prediction | 1h 03m |
Course Name | Online Python Course Bundle |
Deal | You get access to both the 40 courses, 13 Projects. You do not need to purchase each course separately. |
Hours | 215+ Video Hours |
Core Coverage | Python Fundamentals, Linux System Administration with Python, Cryptography, Django Unchained with Python, Python GUI Programming using Tkinter, Rest API with Flask and Python, Python Pyramid Jupyter-IPython Notebook, Violent Python. |
Course Validity | Lifetime Access |
Eligibility | Anyone serious about Python. |
Pre-Requisites | Knowledge of Basics in Any Programming Language would be useful |
What do you get? | Certificate of Completion for each of the courses |
Certification Type | Course Completion Certificates |
Verifiable Certificates? | Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced skills |
Type of Training | Video Course – Self Paced Learning |
System Requirement | 2 GB or above RAM, Open source Python |
Other Requirement | Speaker / Headphone |
To enable great learning experience to all the learners, the course called Python certification training has been designed in such a way that it contains the complete list of courses and all the chapters listed in the form of course curriculum for the Python training with the complete course description of every course and contents in the format of separate chapters. A minimum of 215+ hours is required to complete the Python certification. The below table gives you a complete overview of all the courses and the list of chapters covered in this course content –
The goal of this training to make you learn all the concepts in python and how to debug and test in python by making you work on the projects which are included in the training.
The objective of the training is to cover all the topics related to Python. The some of the concepts which are covered under this training are python fundamentals, Linux system administration with python, Django unchained with python, Advanced Python for IoT & IoT based Data analysis, Cryptography, Matplotlib for Python Developers, Seaborn, PySpark, Data Science and Artificial Intelligence with Python and many other topics are included in this training.
The topics included in this course covers the basic level.
All the topics which are mentioned are explained in detail to give a good knowledge of these concepts.
This training includes many projects to help you to get good hands-on experience in the python language. The undercover projects are:
These are some of the projects which are included in this training.
Python is a high-level and general-purpose programming language and is interpreted. It is of a strong and dynamic type of discipline. It was designed by Guido van Rossum. It has functional, object-oriented and imperative features. It has file extensions such as .py or .pyd or .pyc etc. The code and syntax of Python are highly readable compared to other programming languages. Python is easy to learn, read and maintain and has interactive mode features and provides better scalability and supports GUI applications. It supports structured and functional programming. It was licensed under the Python Software Foundation License. It first appeared in the year 1990. It was influenced by several other programming languages such as C, C++, Java, Haskell, Modula, Perl, etc.
Python has several types of data structures like Lists, Dictionary, Tuples, Strings, Numbers, etc. It has Functions, Modules, Exceptions, File I/O. Python has several libraries for different functionalities, Database and Networking features, Advanced GUI programming, Testing. It has also automatic memory management and garbage collection.
Any Python Developer or Perl Programmer or Web Engineer working on the apps development or back-end web apps development and are also interested and willing to learn Python and its core concepts & advanced concepts should choose this Python courses.
YES, this course can still be considered as an option without any knowledge of computer or Python concepts as this course does not have any pre-requisites of Python basics or Core knowledge in computer programming. Any freshers who are interested in learning Python programming and its core concepts can opt for this course directly without any previous knowledge. The concepts in this course can be easily learned because of the comprehensive content and detailed explanation of the multiple complex programming features of Python.
Yes. this course would add some value to the learners’ profile and also verifiable certifications including different valuable concepts and frameworks of Python.
Yes, this is a quick-fix without any previous knowledge or experience in computers or any programming language but any other programming or scripting language knowledge is highly benefited and added advantage for this course. This Programming Languages course needs a minimum of 215+ hours to be spent to complete the Python courses.
It allowed me to understand Python easily. Since I had some programming background. It allowed me to understand all the basics of python. And was teaching using Python3 and had compared between Python2 and Python3. I suggested those without any background of IT knowledge to watch this video as it was very beginner.
Linked
Very good and very useful for a beginner! I learned a lot.
Very useful and I recommend to those who are interested in Python programming and its world. I’ve been using Python for some time, but I’ve also learned something new about this course.
Great course for beginners. It goes through basic staff in python which will enlighten you on python. There were practical examples used throughout the course which helps a lot in understanding python basics. The course is also useful in laying out a better foundation in understanding python. Awesome course indeed.
An all-around course on Python teaches you the full possibilities of what you can do with the language. I wouldn’t recommend it to people starting to code but is an advantage for the ones who want to learn Python, for whatever application it has, and in this case, there are a lot of applications. Personal fav.
Linked
This Python training is for beginners like me. It is very well presented and I easily understood the topics. The session flow made sense and made it easy to follow the training. From start to finish it was presented at a level where I could understand the topics, which ensured I now have an understanding of Python Programming. Thank you for providing the foundation for Python Programming. I am sure this will assist me in further studies on programming with Python.
Linked
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Courses | No. of Hours | |
---|---|---|
Python for Beginners: 2022 | 3h 22m | |
Python Intermediate Training: 2022 | 3h 34m | |
Python Advanced Training: 2022 | 2h 13m | |
Data Science with Python Training 2022 | 11h 18m | |
Python Programming - 01 | 4h 33m | |
Python Programming - 02 | 3h 06m | |
Python Programming - 03 | 5h 28m | |
Python Programming - 04 | 3h 8m | |
Python Programming - 05 | 4h 22m | |
Python Programming - 06 | 3h 31m | |
Linux System Administration with Python | 13h 9m | |
Python Django | 8h 26m | |
Python Case Study - Instant Markup | 3h 28m | |
Python Django MySQL Case Study - Creating a Blog | 0h 8m | |
Python GUI Programming using Tkinter and Python | 4h 34m | |
Python 3.5 Training | 2h 25m | |
Python Bootcamp | 10h 33m | |
Advanced Python for Data analysis | 6h 28m | |
Python Pyramid - Beginners | 6h 04m | |
Python Pyramid - Advanced | 6h 02m | |
Jupyter-IPython Notebook Training - Beginners | 6h 05m | |
Jupyter-IPython Notebook Training - Advanced | 7h 53m | |
Violent Python | 2h 39m | |
Python Case Study - Cryptography | 5h 11m | |
Matplotlib for Python Developers - Beginners | 4h 12m | |
Matplotlib for Python Developers - Intermediate | 2h 52m | |
Matplotlib for Python Developers - Advanced | 6h 37m | |
Pandas with Python Tutorial | 5h 47m | |
NumPy and Pandas Python | 5h 01m | |
Pandas Python Case Study - Data Management for Retail Dataset | 3h 28m | |
Seaborn Python - Beginners | 2h 28m | |
Seaborn Python - Intermediate | 1h 18m | |
Seaborn Python - Advanced | 1h 56m | |
PySpark Python - Beginners | 2h 3m | |
PySpark Python - Intermediate | 2h 05m | |
PySpark Python - Advanced | 1h 14m | |
Machine Learning with SciKit-Learn in Python | 8h 37m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Machine Learning using Python | 3h 26m | |
Data Science with Python | 4h 14m | |
AI Artificial Intelligence with Python | 6h 15m | |
Video Analytics using OpenCV and Python Shells | 2h 13m | |
Statistics Essentials with Python | 3h 23m | |
Project on Tensorflow - Implementing Linear Model with Python | 1h 46m | |
Project - Data Analytics with Data Exploration Case Study | 5h 7m | |
Project on ML - Random Forest Algorithm | 1h 29m | |
Python Case Study - Sentiment Analysis | 1h 06m | |
Python for Finance | 1h 7m | |
Financial Analytics with Python | 1h 6m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Time Series Analysis in Python - Sales Forecasting | 2h 12m | |
Machine Learning Python Case Study - Diabetes Prediction | 1h 03m |
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