Python Deep Learning | Master Python with Introduction to Data Science
- Description
- Curriculum
Unlock the world of Python programming and data science with our comprehensive course, “Deep Learning into Python with Data Science for Absolute Beginners.” Designed specifically for beginners, this course takes you from the basics of Python to the foundations of data science. Through detailed lessons, hands-on projects, and expert guidance, you’ll gain the skills and confidence to excel in Python programming and data analysis.
What You’ll Learn:
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Getting Started With The Fundamentals of Python Programming: Begin your journey with a solid foundation in Python, understanding its syntax, variables, and data types.
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How to Create Project Files with Basic Python Syntax: Learn to set up and organize your Python projects efficiently, ensuring a smooth workflow.
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Strings In Python Programming: Manipulate and handle text data effectively with Python’s powerful string methods.
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Operators In Python Programming: Master various operators, including arithmetic, relational, and logical operators, to perform complex operations in your programs.
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List In Python Programming: Work with lists to store, access, and manipulate collections of data.
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Tuple In Python Programming: Learn about tuples and how to use them for immutable sequences of data.
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Set In Python Programming: Explore sets and their applications for storing unique elements.
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Dictionary In Python Programming: Understand dictionaries for key-value pair storage and retrieval.
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Decision Making Statements In Python Programming: Implement conditional statements like if, else, and elif to control the flow of your programs.
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Loop Systems In Python Programming: Automate repetitive tasks with for and while loops to enhance your program’s efficiency.
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Functions, Lambda, and Arrays: Create reusable code blocks with functions, utilize lambda expressions for short functions, and work with arrays for efficient data storage.
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Iterators In Python Programming: Learn how to use iterators to traverse through all elements of a collection.
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File Handling In Python Programming: Read from and write to files, enabling data persistence and advanced data management.
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Python Programming Concepts: Delve into advanced Python concepts to enhance your programming skills.
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String Formatting: Format strings for better readability and presentation of your data.
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Object Oriented Programming In Python (OOP): Dive deep into OOP concepts such as classes, objects, inheritance, polymorphism, and encapsulation to create modular and reusable code.
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Introduction to Python for Data Science: Transition into data science with an introduction to its core concepts and applications.
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Python Libraries for Data Science: Explore essential Python libraries for data science, including NumPy, Pandas, and Matplotlib.
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NumPy Library: Learn to perform numerical operations and handle arrays with NumPy.
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Pandas Library: Master data manipulation and analysis using the Pandas library.
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Matplotlib Library: Visualize data effectively with Matplotlib’s powerful plotting capabilities.
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Sampling Data in Data Science: Understand the importance of sampling and how to sample data for analysis.
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How to Read Data: Learn various methods to read data from different sources.
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How to Sample Data: Implement sampling techniques to work with subsets of your data.
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Read Data from External Files: Import data from external files into your Python programs.
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Data to CSV and TXT Formats: Save and export your data in CSV and TXT formats for easy sharing and analysis.
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Convert and Read Data in CSV Format: Convert your data into CSV format and read CSV files in Python.
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Convert TXT File to Table: Transform text files into tabular data for easier analysis.
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Data Preparation in Data Science: Prepare your data for analysis by cleaning, transforming, and organizing it.
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Series Data Structure: Work with Pandas Series for one-dimensional labeled data.
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Data Frame Structure: Master Pandas DataFrames for two-dimensional labeled data structures.
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And Many More: Continue to build your skills with additional topics and projects designed to reinforce your learning and prepare you for real-world challenges.
Why Enroll in This Course?
- Comprehensive Curriculum: Covering all essential topics from Python basics to data science, ensuring a thorough understanding and skillset.
- Hands-On Projects: Gain practical experience with real-world projects that solidify your learning.
- Beginner-Friendly: No prior programming experience required, making this course accessible to everyone.
- Expert Instruction: Learn from experienced instructors who provide clear explanations and step-by-step guidance.
- Lifetime Access: Revisit course materials anytime and learn at your own pace.
- Community Support: Join a community of learners to share knowledge, seek help, and collaborate on projects.
By the end of this course, you’ll have the confidence and skills to tackle any Python programming and data science challenge, positioning you for success in the industry. Enroll now and start your journey to becoming a Python programming and data science expert!
Knowlegde Base:
Python programming course, learn Python programming, data science for beginners, Python basics, Python data structures, Python strings, Python operators, Python loops, Python functions, Python OOP, Python file handling, Python data science libraries, NumPy, Pandas, Matplotlib, data sampling, data preparation, Python data analysis, master Python programming, beginner to advanced Python programming.
No basic knowledge of computer programming is required for this course.
You must have a good computer system. A computer (Windows/Mac/Linux).
You’ll need to install Anaconda. We will show you how to do that step by step.
Anyone who wants to learn to code..
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
You should take this course if you want to become a Data Scientist or if you want to learn about the field.
