Learn Python, NumPy, and Pandas from Scratch
What you will learn
Python Basics: A solid foundation in Python programming, including data types, loops, conditionals, functions
Understanding Lists are different from arrays
NumPy Fundamentals: Understanding the NumPy library to efficiently work with arrays, matrices, and perform mathematical operations.
Pandas Essentials: Exploring the Pandas library in-depth, covering Series and DataFrames, data importing/exporting, data cleaning, filtering, sorting, grouping
Add-On Information:
Get Instant Notification of New Courses on our Telegram channel.
Noteβ Make sure your ππππ¦π² cart has only this course you're going to enroll it now, Remove all other courses from the ππππ¦π² cart before Enrolling!
- Embark on your data science journey with a no-prior-experience-needed approach to Python, the powerhouse language for analytics.
- Discover the building blocks of computation, moving beyond simple numbers to structured, multi-dimensional data handling.
- Grasp the essence of sequential data structures and differentiate them from their fixed-size, homogeneous counterparts.
- Unlock the potential of vectorized operations for lightning-fast numerical computations, a crucial skill for any data professional.
- Demystify the process of loading diverse datasets into memory, paving the way for insightful analysis.
- Develop a keen eye for identifying and rectifying imperfections within your data, ensuring the integrity of your findings.
- Acquire the ability to extract specific subsets of your data based on complex criteria, honing your data selection skills.
- Learn to arrange your data in meaningful orders, facilitating pattern recognition and hypothesis testing.
- Master the art of aggregating and summarizing data, transforming raw information into actionable insights.
- Gain proficiency in transforming raw data into readily analyzable formats, bridging the gap between raw inputs and meaningful outputs.
- Understand the critical role of efficient memory management when dealing with large datasets, a key performance consideration.
- Build the confidence to tackle real-world data challenges by mastering foundational tools used by industry professionals.
- Acquire a transferable skillset applicable to a wide range of fields that rely on data analysis and manipulation.
- Pros:
- Designed for complete novices, ensuring a gradual and supportive learning curve.
- Focuses on the most essential libraries for practical data analysis, providing immediate utility.
- Builds a strong conceptual understanding alongside practical coding skills.
- Cons:
- May not delve into advanced or specialized applications of Python, Pandas, or NumPy.
English
language