An extraordinary elevated level, object-oriented programming language. Composing programs in Python takes less time compared to other languages. Django is a free and open-source Web Framework in Python that supports quick turn of events, clean & programmatic plans.
Python Programming Course in Kochi
Overview
Techmindz comprehensive Python training course will teach you python fundamentals, data operations, conditional statements, shell scripting, and Django. Our team leads will give you hands-on development experience and prepare you for an exciting career as a professional python programmer.
Career Opportunities in Python
- Python Developer
- Product Manager
- Data Analyst
- Data Journalist
- Research Analyst
- Data Scientist
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This course includes
Seed Plan
- Duration 2.5 months
- 0.5 Skill training
Benefits
- Certified course
- Internship based on PE
- 8 Grooming sessions
- Performance evaluations
- Recorded sessions
- Extra learning sessions
- Weekly assignments
- Main Project
- Free Access to LMS
- Update on Job vacancy in and around Infopark
Growth Plan
- Duration 2.5 months
- 0.5 months training
- 3 months internship
Benefits
- Certified course
- ∙ Confirmed Paid Internship
- Sessions by Industry Experts
- Flexible pricing options
- 24x7 learner assistance and support
- Placement based on PE
- 8 Grooming sessions
- Performance evaluations
- Recorded sessions
- Extra learning sessions
- Weekly assignments
- Main Project
- Free Access to LMS
- Update on Job vacancy in and around Infopark
Success Plan
- Duration 2.5 months
- 0.5 months training
- 3 months internship with stipend
- job placement
Benefits
- Assured Placement
- Certified course
- Confirmed Paid Internship
- Sessions by Industry Experts
- Live client Projects
- Flexible pricing options
- 24x7 learner assistance and support
- 8 Grooming sessions
- Performance evaluations
- Recorded sessions
- Extra learning sessions
- Weekly assignments
- Main Project
- Free Access to LMS
- Update on Job vacancy in and around Infopark
Python
Syllabus:
Accordion Content
- What is Python?
- Knowing the history of Python
- Unique features of the Python language
- Differences between Python 2 and Python 3
- Installation of Python and Environmental Setup
- First Python Program
- Python Identifiers
- Python Keywords
- Python Indentation
- Document and Comments Interlude in Python
- Command-line arguments
- Getting to know User Input
- Python Basic Data Types
- What are the variables?
- Introduction
- Lists in Python
- Knowing more about Lists
- Understanding the Iterators
- Generators and Comprehensions
- Lambda Expressions
- Understanding and using the Ranges
- Knowing about the section in Python
- Python Dictionaries
- Understanding more Dictionaries
- Sets
- Python Sets Examples
- Reading Files
- Writing text files
- Appending to Files and Challenge
- Manually writing the binary files
- Writing Binary files with Pickle
- Python user-defined functions
- Python packages and functions
- Calling and Defining the function
- The anonymous Functions
- Statement and Loops in Python
- Python Packages & Modules
- Overview of OOP
- Creating Objects and Classes
- Accessing attributes
- Built-In Class Attributes
- Destroying Objects
- What is Exception?
- Handling the exception
- Try..except..else
- try-finally clause
- The argument of the Exception
- Standard Python Exceptions
- User-Defined Exceptions
- Raising an exceptions
- What is a regular expression?
- Knowing match Function
- Understanding the search Function
- Searching Vs Matching
- Extended Regular Expressions
- Search and Replace function
- Wildcard
- Collections – named tuples, default dicts
- Breakpoints and Debugging
- Using IDEs
- Matching vs searching
Django Course Syllabus:
Accordion Content
- Installation of Django
- Module Settings
- Requests and Responses
- Running the development server
- Introduction to Django Admin Site
- Introduction to Model
- Field Types
- Field customization
- Making queries
- Accessing the related objects
- Django migrations
- Raw SQL and search
- View functions
- URLConfs
- Shortcuts and decorators
- Request and Response objects
- File upload
- Class-based views
- Mixins
- Generating PDF and CSV
- Overview of the template language
- Built-in tags
- Built-in filters
- Humanization
- Custom tags
- Custom filters
- csrf token
- Introduction
- Forms API
- Validating forms
- Built-in fields
- Built-in widgets
- Model form
- Form sets
- Types of vectors
- Internationalization
- Localization
- Localizing UI
- Form inputs
- Model form
- Time zones
- Form sets
- Authentication
- Django built-in authentications
- Customizing authentication
- Password management
- Logging
- Caching
- Sending email
- Syndication feeds (RSS/Atom)
- Pagination
- Serialization
- Message framework
- Sessions
- Site maps
- Signals
- Static file management
- Introduction to bootstrap framework
- Bitly – a URL shortening service similar to bitly.com
- Twitter – Clone of twitter site
Data Science Syllabus:
Accordion Content
- Reading the Data, Referencing in formulas , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering
- Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security
- VBA Macros, Ranges and Worksheet in VBA
- IF conditions, loops, Debugging, etc.
- Introduction to Statistics
- Measures of central tendencies
- Measures of variance
- Measures of frequency
- Measures of Rank
- Basics of Probability, distributions
- Conditional Probability (Bayes Theorem)
- Sets & Functions
- Introduction to Linear Algebra
- Matrices Operations
- Introduction to Calculus
- Derivatives & Integration
- Maxima, minima
- Area under the curve
- Overview of Python- Starting with Python
- Why Python for data science?
- Anaconda vs. python
- Introduction to installation of Python
- Introduction to Python IDE’s(Jupyter,/Ipython)
- Concept of Packages – Important packages
- NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc
- Installing & loading Packages & Name Spaces
- Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
- List and Dictionary Comprehensions
- Variable & Value Labels – Date & Time Values
- Basic Operations – Mathematical/string/date
- Control flow & conditional statements
- Debugging & Code profiling
- Python Built-in Functions (Text, numeric, date, utility functions)
- User defined functions – Lambda functions
- Concept of apply functions
- Python – Objects – OOPs concepts
- How to create & call class and modules?
- What is NumPy?
- Overview of functions & methods in NumPy
- Data structures in NumPy
- Creating arrays and initializing
- Reading arrays from files
- Special initializing functions
- Slicing and indexing
- Reshaping arrays
- Combining arrays
- NumPy Maths
- What is pandas, its functions & methods
- Pandas Data Structures (Series & Data Frames)
- Creating Data Structures (Data import – reading into pandas)
- Descriptive vs. Inferential Statistics
- What is probability distribution?
- Important distributions (discrete & continuous distributions)
- Deep dive of normal distributions and properties
- Concept of sampling & types of sampling
- Concept of standard error and central limit theorem
- Hypothesis Testing & Applications
- Statistical Methods – Z/t-tests (One sample, independent, paired), ANOVA, Correlation and Chi- square
- Python user-defined functions
- Python packages and functions
- Calling and Defining the function
- The anonymous Functions
- Statement and Loops in Python
- Python Packages & Modules
- Applications of Machine Learning
- Supervised vs Unsupervised Learning vs. Reinforcement Learning
- Overall process of executing the ML project
- Stages of ML Project
- Concept of Over fitting and Under fitting (Bias- Variance Trade off) & Performance Metrics
- Concept of feature engineering
- Regularization (LASSO, Elastic net and Ridge)
- Types of Cross validation(Train & Test, K-Fold validation etc.)
- Concept of optimization – Gradient descent algorithm
- Cost & optimization functions
- Python libraries suitable for Machine Learning
- Text Mining – characteristics, trends
- Text Processing using Base Python & Pandas, Regular Expressions
- Text processing using string functions & methods
- Understanding regular expressions
- Identifying patterns in the text using regular expressions
- Vectorization (Count, TF-IDF, Word Embedding’s)
- Sentiment analysis (vocabulary approach, based on Bayesian probability methods)
- Name entity recognition (NER)
- Methods of data visualization
- Length counts plot
- Word frequency plots
- Word clouds
- Correlation plots
- Letter frequency plot
- Heat map
- Grouping texts using different methods
- Language Models and n-grams — Statistical Models of Unseen Data (Smoothing)
- Wildcard
- Modern era of AI
- Role of Machine learning & Deep Learning in AI
- Hardware for AI (CPU vs. GPU vs. FPGA)
- Software Frameworks for AI & Deep Learning
- Key Industry applications of AI
- What are the Limitations of Machine Learning?
- What is Deep Learning?
- Advantage of Deep Learning over Machine learning
- Reasons to go for Deep Learning
- Real-Life use cases of Deep Learning
- Overview of important python packages for Deep Learning
- Overview of Neural Networks
- Activation Functions, hidden layers, hidden units
- Illustrate & Training a Perceptron
- Important Parameters of Perceptron
- Understand limitations of A Single Layer Perceptron
- Illustrate Multi-Layer Perceptron
- Understand Backpropagation – Using Example
- Implementation of ANN in Python- Keras
- What is Cloud Computing? Why it matters?
- Traditional IT Infrastructure vs. Cloud Infrastructure
- Cloud Companies (Microsoft Azure, GCP, AWS ) & their Cloud Services (Compute, storage, networking, apps, cognitive etc.)
- Use Cases of Cloud computing
- Over view of Cloud Segments: IaaS, PaaS, SaaS
- Overview of Cloud Deployment Models
- Overview of Cloud Security
- AWS vs. Azure vs. GCP
- What is MLOps
- MLOps vs. DevOps vs. Data Engineering
- Why MLOps is important?
- ML Engineering Pipeline
- How to implement MLOps?
- Understand end to end MLOps solution
Description
Python is an extraordinary elevated level, object-oriented programming language. Composing programs in Python takes less time compared to other languages. Django is a free and open-source Web Framework in Python that supports quick turn of events, clean and programmatic plans. Techmindz comprehensive Python training course will teach you python fundamentals, data operations, conditional statements, shell scripting, and Django. Our team leads will give you hands-on development experience and prepare you for an exciting career as a professional python programmer.
Why should You Learn Python?
Over the previous few years, the expansion of the Python language is tremendous, and also the opportunities in Python are increasing rapidly. By learning Python, you will enter multiple areas like Data Analytics, Data Science, Web Development, Machine Learning, Data science, etc. Techmindz’s Python Training at Infopark Cochin will help you figure in multiple domains with our world-class training methodology and evaluation systems. By moving to advanced python programming training, a candidate is giving a strong foundation to his python career.
Who can Learn Python?
Writing computer programs is founded on the rationale. If you have the incredible feeling of motivation, you can begin with practically any language. Regarding coherence of code, PYTHON is probably the least demanding language as it needs fewer code lines. Suppose you know any programming language like c,c++, java, ruby, etc. its straightforward to adapt to Python. Techmindz python certification course enables both a fresher and a professional to enter into the Python world through our unique learning tactics. A lot of ways to learn Python are available now. Either you can enroll for Python online course or a python crash course and take a python certification. The next best way to learn Python is the videos you can get by searching “Python tutorials for beginners.” You can achieve it in Techmindz.
How much a Python developer earns?
The average salary of a Python developer is ₹708,012. Entry-level data scientists with 1 to 4 years experience get around Rs. 413 K per annum. It will vary up to 1,150,000 in India.
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