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The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements
• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods
• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions
• Decorators
• Generators
• Context Managers
• Metaclasses
• Inheritance and Polymorphism
• Encapsulation and Abstraction
• Class methods and static methods
• Special (magic/dunder) methods
• Property decorators - getters, setters, and deletes
• Working with files
• Reading and writing files
• Buffered read and write
• Other file methods
• Logging & Debugger
• Modules and import statements
• SQL Basics
• Creating DB Table
• INSERT, READ, UPDATE, DELETE
• Introduction to MongoDB
• CRUD operations in MongoDB
• namedtuple(), deque, ChainMap,
• Counter, OrderedDict, defaultdict,
• UserDict, UserList, UserString
• Exceptions handling with try-except
• Custom exception handling
• List of general use exception
• Best practice exception handling
• Generators, Iterators
• The Functions any and all
• With Statement
• Data Compression
• A Daytime Server
• Clients and Servers
• The Client and Server Programs
• Classes and Threads
• Multi-threading; thread life cycle
• Regular Expression Syntax
• Group, Split and wildcards
• Quantifiers
• Match, Search and Find all methods
• Character Sequence
• Introduction to OpenCV, Installation
• Basic Operations on Images
• Image Filtering
• Image Classification
• Introduction to GIT
• Basic Git commands
• Introduction to Flask and Installation
• Creating project
• Routing,templates, forms and database integration
• Deployment on render
• Django Introduction and Installation
• Creating a Project
• Django Architecture and File Structure
• Folder Structure, First Django project
• Database and Views, Static Files and Forms
• URL Mapping and Routing
• Defining Models and Relationships
• Database Migrations and Schema Changes
• Querying Data using Django ORM
• Model Forms and Form Validation
• HTML Forms in Django
• Model Forms and Form Validation
• Formsets and Inline Formsets
• File Uploads and Validation
• Deploying Django Applications
• Hosting Options (e.g., Heroku, AWS)
• Project Showcasing and Review
Python stands out as a dynamic, high-level language esteemed for its adaptability and versatility across diverse domains.
Setting up Python involves obtaining the installer from the official website and following the installation instructions provided.
Preference between Python and Java varies depending on the context; Python shines for its simplicity and ease of learning, while Java excels in performance and scalability, particularly in enterprise settings.
Python 2 has ceased development and support, while Python 3 continues to evolve, introducing syntax improvements and new functionalities.
Novices can effectively learn Python through online tutorials, interactive coding platforms, literature resources, and active involvement in coding communities.
Python proves indispensable in data science endeavors, leveraging libraries like Pandas, NumPy, and scikit-learn for tasks ranging from data manipulation to machine learning.
Python frameworks provide developers with pre-existing code and libraries to expedite development efforts in specific domains, such as web development (e.g., Django, Flask) or GUI applications (e.g., Tkinter).
Proficient debugging involves techniques like strategic print statements, utilization of debugging tools such as PDB or IDE debuggers, and thorough analysis of error messages.
Python offers greater versatility, catering to a wider range of applications, while R specializes in statistical analysis with richer packages tailored specifically for such tasks.
In Mexico, the demand for Python developers has steadily increased, driven by Python's prevalence in web development, data science, and automation.
Employers typically seek Python developers with a strong grasp of fundamental concepts, adept problem-solving skills, familiarity with frameworks/libraries, and the ability to write efficient, maintainable code.
While certifications validate skills, employers often prioritize practical experience and demonstrable projects over certifications.
An impactful resume should showcase relevant projects, highlight problem-solving abilities, and emphasize technical skills and achievements relevant to the role.
Effective preparation involves revisiting algorithms, practicing coding challenges, and demonstrating a comprehensive understanding of Python principles and best practices.
While beneficial, practical skills and experience often carry more weight, making academic qualifications optional for many roles in Python development.
Primary responsibilities include application development, algorithm implementation, issue troubleshooting, and collaboration with team members to achieve project goals.
Transitioning involves acquiring relevant skills through courses or self-study, building a project portfolio, and networking within the industry.
Python is widely used for data manipulation, analysis, visualization, machine learning, and statistical modeling, owing to its versatile libraries.
Python is widely used for data manipulation, analysis, visualization, machine learning, and statistical modeling, owing to its versatile libraries.
Python plays a crucial role in AI applications such as natural language processing, computer vision, machine learning algorithms, and neural network development due to its simplicity and powerful libraries.
Major corporations like Google, Facebook, Amazon, and Netflix extensively utilize Python across various operations including web development, data analysis, automation, and machine learning initiatives.
The Python developer's salary in Mexico ranges from MXN 119,681 per year according to an Indeed report.
DataMites stands out as your ideal partner for mastering Python in Mexico, offering a comprehensive curriculum, seasoned instructors, and adaptable teaching methodologies. Whether you're a novice or aiming to advance your Python skills, DataMites provides practical learning experiences through hands-on projects and dedicated placement assistance to elevate your career prospects significantly.
Choosing Python training in Mexico with DataMites ensures immersion in a meticulously crafted program tailored to excel in the dynamic programming landscape, closely aligning with industry demands. The emphasis on hands-on learning guarantees the acquisition of relevant skills essential for success in the field.
The Python developer course at DataMites in Mexico typically spans four months, comprising 20 hours of live online sessions supplemented by 400 hours of self-paced learning opportunities.
DataMites welcomes individuals from diverse educational backgrounds, including graduates, postgraduates, and high school graduates, to enroll in the Python developer training in Mexico. The program is designed to accommodate beginners, focusing on establishing a robust foundation in Python fundamentals.
The Flexi-Pass feature for Python training offered by DataMites provides participants with a flexible three-month window to access training sessions. This flexibility allows learners to address queries, review material, and attend additional sessions as needed to effectively achieve their learning objectives.
The DataMites Certified Python Developer course in Mexico delivers comprehensive training covering fundamental to advanced Python concepts, empowering participants with proficient Python skills tailored to meet industry standards.
The Python for Data Science course caters to individuals with varying levels of programming proficiency, covering essential concepts such as data manipulation, machine learning algorithms, and programming techniques crucial for data analysis, regardless of prior experience.
The Data Mining with Python course delves into techniques for extracting insights from extensive datasets to drive predictive analytics, a critical aspect of Data Science that demands diverse skills and knowledge for effective data analysis.
The Python for Machine Learning Course provided by DataMites in Mexico offers a comprehensive introduction to Python tailored specifically for machine learning applications. Participants gain proficiency in various machine learning algorithms and their practical implementation using Python, particularly leveraging the Scikit-Learn package.
The Deep Learning with Python Course explores deep learning principles using Python and the Keras library, covering both theoretical concepts and practical applications in domains such as computer vision, natural language processing, and generative models.
The cost for Python training in Mexico at DataMites varies, typically ranging from MXN 2,725 to MXN 7,460, offering flexible options to suit different learning preferences and budgets.
DataMites offers Python courses with internship opportunities in Mexico, enabling participants to gain invaluable real-world experience and apply their Python skills in professional environments, thus enhancing their career prospects.
Upon successful completion of Python classes at DataMites in Mexico, participants receive the esteemed IABAC® certification, globally recognized for validating competence in Python programming, enhancing their credentials in the job market.
Participants are required to bring valid photo identification, such as a National ID card or driver's license, to Python training sessions in Mexico for verification purposes and to ensure a smooth registration process.
Yes, DataMites integrates project work into its Python training curriculum in Mexico, offering participants opportunities to undertake 10 capstone projects and 1 client project. These projects serve as practical applications of Python skills, allowing participants to demonstrate proficiency in real-world scenarios.
For participants unable to attend Python training sessions in Mexico, DataMites offers access to recorded sessions and course materials online. Additionally, makeup sessions can be scheduled to ensure uninterrupted learning progress.
Python developer training in Mexico at DataMites covers a comprehensive array of tools including Anaconda, Python, PyCharm, Flask, NumPy, Pandas, and Google Colab, equipping participants with a diverse skill set necessary for professional Python development.
Yes, prospective participants have the opportunity to attend a complimentary demo class, providing them with a firsthand glimpse into the training program and allowing them to gauge its suitability before committing.
Career mentoring sessions conducted by the DataMites Placement Assistance Team (PAT) serve to guide participants on potential career paths within Data Science, addressing challenges and furnishing strategies for navigating the corporate landscape successfully.
Yes, DataMites offers assistance sessions tailored to address queries and provide clarity on specific Python topics, ensuring participants grasp key concepts thoroughly and progress effectively in their learning journey.
DataMites offers a range of payment options including cash, credit card, net banking, check, debit card, and PayPal, providing participants with flexibility and convenience in payment processing.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
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