Certification Course in Core Python
- Get Trained by Trainers from ISB, IIT & IIM
- 40 Hours of Intensive Classroom & Online Sessions
- 60+ Hours of Practical Assignments
- Industry Placement Training
- Job Placement Assistance
Used by the top 25 unicorn companies in the US, Python is among the top programming languages that have governed the world of engineers, programmers, and developers. It is an interactive, dynamic, and versatile language that supports structured, object-oriented, and functional programming which also contributes to one of the major reasons for its popularity. It is considered a purely production-based language used for first-class projects by enterprises and enjoys an epic community of developers. The giant organizations using Python include NASA, Google, IBM, etc. who use it for varied applications. Level up your Python skills to the core with the’ Core Python’ training from Datamaze and prepare for a bright future.
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Core Python Course Overview
Python is among the most leveraged and favoured programming languages used by Data Scientists worldwide. Master the fundamentals of this demanding language and get hands-on practical experience with the functional applications of Python. Learn Python Data Structures, Dictionaries & Sets. Explore various Python Packages for analysing data and dive into advanced theoretical concepts like Multi-Threading, Exception Handling, Writing Scripts, Sequence, and File operations in Python. In this course acquire all the grounding in the key concepts of Python and understand the fundamentals of Python programming as well as knowledge of object-oriented programming in Python. This course focuses to provide a thorough understanding of Python as a programming language which is also a highly paid skill in the tech arena. So, join the ‘Core Python’ course to become an expert in Python and avail the highest number of job opportunities in this field.
What is Python?
It is a general-purpose language that is easier to learn and approach making it suitable for several tasks from specific fields to general. It is a highly flexible and extensible language that caters to the needs of web developers, engineers, analysts and is backed by an active community of programmers. It is great for scripting and comes with numerous testing frameworks and plenty for Data Visualization.
Who should signup?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
- Math, Science and Commerce Graduates
Learning Outcomes of Core Python Course
Python is regarded as an embedded scripting language that is used for web development, data science, and cloud operations. In this course, students will use Python for statistical analysis and Data Visualization along with exploring and understanding the core programming features like data structures, conditionals, loops, variables, and functions. They will also gain an understanding of the application of coding and will be able to create, run, and debug a code. They will also understand the fundamentals of Python from syntax to modules. The students will also learn to write loops and decision statements. They will learn the use of Python classes to design object-oriented programs. They will also be introduced to the advanced techniques leveraged to implement sophisticated frameworks like Django along with an introduction to concurrent and parallel programming. So, enrol for the Core Python training at 360DigiTMG which is designed for students, software engineers, systems analysts, program managers, and support personnel. In this course, you will-
- Understand the fundamentals of Functional Oriented Programming Languages
- Understand the fundamentals of Python Programming Language
- Get a broad insight into writing programs
- Learn to design and program Python applications
- Understand the application of coding
Training Modules of Core Python
Python is considered to be a flexible, powerful object-oriented, and an interpreted language with a wide range of applications that includes Data Science, Data Analytics, Big Data, and also developing various games and web applications. These modules on ‘Core Python’ will expand your concepts and introduce you to tools that will enhance your Python palette. The modules begin with an introduction to Python Programming with the Installation of Python & Associated Packages. The modules go on to explore the concepts of Python like data types, data structures, tuples, lists, basic operators, functions, GUIs, regular expressions, conditional statements, networking, and much more. The modules also give an in-depth understanding of Database Programming and connectivity to various Data Sources along with an Extensive coverage of Django Framework.
- Introduction to Python Programming
- Installation of Python & Associated Packages
- Graphical User Interface
- Installation of Anaconda Python
- Setting Up Python Environment
- Data Types
- Operators in Python
- Arithmetic operators
- Relational operators
- Logical operators
- Assignment operators
- Bitwise operators
- Membership operators
- Identity operators
- Data structures
- Vectors
- Matrix
- Arrays
- Lists
- Tuple
- Sets
- String Representation
- Arithmetic Operators
- Boolean Values
- Dictionary
- Conditional Statements
- if statement
- if – else statement
- if – elif statement
- Nest if-else
- Multiple if
- Switch
- Loops
- While loop
- For loop
- Range()
- Iterator and generator Introduction
- For – else
- Break
- Functions
- Purpose of a function
- Defining a function
- Calling a function
- Function parameter passing
- Formal arguments
- Actual arguments
- Positional arguments
- Keyword arguments
- Variable arguments
- Variable keyword arguments
- Use-Case *args, **kwargs
- Function call stack
- Locals()
- Globals()
- Stackframe
- Modules
- Python Code Files
- Importing functions from another file
- __name__: Preventing unwanted code execution
- Importing from a folder
- Folders Vs Packages
- __init__.py
- Namespace
- __all__
- Import *
- Recursive imports
- File Handling
- Exception Handling
- Regular expressions
- Oops concepts
- Classes and Objects
- Inheritance and Polymorphism
- Multi-Threading
- List Comprehensions
- List comprehension
- Dictionary comprehension
- Enumerate
- Zip and unzip
- Generator Expressions
- Tuples – Nested, Names, Unpacking
- Splitting – Slicing Objects, Ellipsis
- Augmented Assignments with Sequences
- Build-in Sort Functions
- Ordered Sequences with Bisect
- Arrays, Memory Views, Deques
- Handling Missing Keys
- Set Theory, Variations, Operations
- Higher-Order Functions
- Function Annotations
- Functional Programming Packages
- Procedural vs Functional
- Pure functions
- Map()
- Reduce()
- Filter()
- Lambdas
- Loop vs Comprehension vs Map
- Identify, Equality & References
- MySQL db Module
- INSERT, READ, DELETE, UPDATE, COMMIT, ROLLBACK operations on SQL using Python
- Python Packages
- Pandas – Series, Dataframes
- Numpy – Arrays, Memory, Matrices, Broadcasting, Masked Arrays
- Scipy
- Matplotlib
- Seaborn
- Sklearn (Scikit Learn)
- Statsmodels
- Jupyter Notebooks, IPython Notebooks
- Data Collection using CSV, JSON, XML, HTML & Scrapping
- Data Wrangling
- Understanding
- Filtering
- Typecasting
- Transformations & Normalization
- Imputation
- Handling Duplicates & Categorical Data
- Data Summarization
- Data Visualizations using Python Packages
- Line Chart
- Bar Chart
- Histogram
- Pie Charts
- Box Plots
- Scatter Plots
- Figures & Subplots
- Additional Visualization Packages – bokeh, ggplot, plotly
- Python XML and JSON parsers
- Basic Images Processing using Python OpenCV
- Dates and Times
- Binary Data
- Pythonic Programming
- Exception Handling
- Purpose of Exception Handling
- Try block
- Except block
- Else block
- Finally block
- Built-in exceptions
- Order of ‘except’ statements
- Exception – mother of all exceptions
- Writing Custom exceptions
- Stack Unwinding
- Enhancing Classes
- Metaprogramming
- Developer Tools
- Unit Testing with PyTest
- Multi-Threading
- Program Memory Layout
- Concurrency
- Parallelism
- Process
- Thread of execution
- Creating a thread
- Joining a thread
- Critical section
- Locks
- PyQt
- Network Programming
- Scripting for System Administration
- Serializing
- Advanced-Data Handling
- Implementing Concurrency
- Asynchronous programming
- The asyncio framework
- Reactive programming
- Parallel Processing
- Introduction to parallel programming
- Using multiple processes
- Parallel Cython with OpenMP
- Automatic parallelism
- Introduction to Concurrent and Parallel Programming
- Technical requirements
- What is concurrency?
- Not everything should be made concurrent
- The history, present, and future of concurrency
- A brief overview of mastering concurrency in Python
- Setting up your Python environment
- Django with REST Webservices
- Client-Server architecture
- Web Application
- Web framework
- Installing Django modules
- Creating first basic Django
- Creating Model classes
- Django Template tags and template programming
- Django rest framework
- Understanding REST Architecture
- HTTP GET, POST
- JSON serialization
- Writing REST API
- Web Extraction
- Beautiful Soup
- Selenium
- Serialization pickling, XML & JSON
- Introduction to Serialization
- Structure and Container
- Pickle Module
- pickling built-in data structures
- byte strings
- binary
- xml parsing and construction – xml
- json parsing and construction – json, simplejson
- Logging
- Purpose of logging
- Logging levels
- Types of logging
- Logging format
- Logging Handlers
- Disadvantages of excessive logging
- Custom loggers
Tools Covered
Core Python Course Training Trends
Python will complete three decades and has seen massive growth in its demand and is the second most popular programming language that can also be integrated with other languages. Its extensive libraries are useful in machine learning and artificial intelligence which include NumPy, TensorFlow, and Pandas. One of the biggest advantages of Python Language is the fact that it is simple and easy to adopt and has proved to be a game-changer for Data Scientists. The language is used to build dynamic mobile and desktop applications along with programs that can run on several operating Platforms.
Some of the trends we will see in the language will be the updates in its framework and libraries that will expand its capacity and make it more beneficial and exceptional. With advancements in analytics, enterprises will take up more data mining projects that will help increase the overall efficiency of the business. We shall also witness significant use of python in cloud computing, creating faster codes and automation tasks. With the combination of flexibility and increased privacy protection, it will continue to play a significant role in the future too and will maintain its position as the most popular programming language among developers.
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