Lvl.1 -> Python Wrangler
Pre-requisite: N/A (This path is suitable for beginners)
Approx. Time Required: 3 months
✅ NEW! Join our Mentorship Program for this Career Path here. 👈
This comprehensive pathway is designed to take you from beginner to pro in Python, equipping you with all the tools necessary to excel in data science, analysis, and programming. You’ll learn through real exercises, building a robust foundation in core programming principles, exploring advanced data manipulation with pandas 🐼, and diving deep into statistical analysis.
Throughout this path, you’ll also learn to integrate Python with other powerful tools and libraries, such as NumPy, Seaborn, Matplotlib, and more. You’ll emerge with the confidence to tackle complex data analysis tasks, automate data processes, and contribute meaningfully to data-driven decision-making. Whether you aim to enter the field of data science or enhance your current skill set, this path will solidify your Python expertise and help you stand out in the tech industry.
Begin your journey by mastering core programming concepts, data structures like lists and dictionaries, and the foundational statistical concepts crucial for data science.
Learn how to manipulate data frames and perform advanced visualizations, setting the stage for complex data analysis tasks.
Engage in hands-on projects, from creating simple Python games to complex data analysis, ensuring you apply your learning in practical scenarios.
2.Python 3 Programming: Beginner to Pro Masterclass
Transition from beginner to intermediate Python use with focused lessons on functions, loops, and conditional logic.
Tackle real-world problems and learn Python’s applications in various industries through interactive projects.
Explore advanced features of Python programming, such as lambda expressions and file handling, to enhance your coding repertoire.
3. Python for Statistical Analysis
Dive into probability, distributions, and hypothesis testing with Python to understand and perform statistical analysis on various datasets.
Learn to conduct hypothesis tests, work with sampling distributions, and understand the central limit theorem with practical Python applications.
Explore and analyze datasets to uncover insights and prepare for machine learning and predictive modeling.
Plus, check out these Live Lab Recordings:
👉 Remember to join the Mentorship Program [here] to grow even faster!