Learning Core Python Fundamentals at Global Quest Technologies

Day 20/30 – Python Basics for Data Analytics Today I started learning Python basics, which is an important step in data analytics. Python is easy to understand and widely used in the data field. It helps in handling data, performing calculations, and automating tasks. I learned about variables, which are used to store values. Understanding data types like integers, strings, and floats is very important. I also explored data structures like lists, tuples, dictionaries, and sets. Each data structure is useful in different situations. Lists are flexible and commonly used. Tuples are used when data should not be changed. Dictionaries help store data in key-value format. Sets are useful for storing unique values. I also learned about conditions to make decisions in code. Loops help repeat tasks and save time. Python makes complex tasks simple and easy to manage. It is very useful for real-world data analysis. Practicing basics is important before moving to advanced topics. Today’s learning helped me build a strong foundation. I am excited to explore more in Python and data analytics. Fortune Cloud Technologies Private Limited #fortunecloud #BTMLayout #BengaluruIT #BengaluruStudents #DataAnalytics #Python Thank you Fortune Cloud Technologies Private Limited

🚀 Day 2 of My Python Learning Journey | Comments & Variables Consistency is powerful. Even small steps in learning can build strong foundations over time. Today, on Day 2 of learning Python, I explored two very important concepts: Comments and Variables. 🔹 Comments in Python Comments help explain the logic behind the code. They make programs easier to understand, especially when working on large projects or collaborating with others. 🔹 Variables in Python Variables act like containers that store information which can later be used in a program. While learning, I also discovered some important rules for naming variables: ✔️ A variable must start with a letter or underscore (_) ✔️ It cannot start with a number ✔️ No spaces are allowed in variable names ✔️ Python is case-sensitive (for example, name and Name are different) ✔️ We cannot use Python keywords like print as variable names What I found especially interesting is how variables play a crucial role in Data Analysis. They help in: 📊 Storing customer information 📊 Calculating totals and averages 📊 Counting missing values in datasets 📊 Storing columns during data cleaning 📊 Renaming columns dynamically 📊 Applying filter conditions to analyze data As someone transitioning into the world of Data Analytics, learning these fundamentals is helping me build a strong base for working with data using Python. I’m documenting my journey step by step because I believe learning in public keeps you accountable and inspires others who are starting from scratch. A big gratitude to @Satish Dhawale from SkillCourse for explaining these concepts in such a beginner-friendly way. 🙏 Looking forward to sharing Day 3 soon! 🚀 #Python #DataAnalytics #LearningJourney #AspiringDataAnalyst #PythonForDataAnalysis #WomenInTech #ContinuousLearning

Day 14 My Python Full Stack Development Journey Today’s learning focused on two important Python data structures: Sets and Dictionaries. These are powerful tools for handling data efficiently in real-world applications. 🔹 Sets – Key Learnings • A set is an unordered collection of unique elements • Does not allow duplicate values • Defined using {} or set() • Supports heterogeneous data types ✅ Operations practiced: • Adding elements → add() • Removing elements → remove(), discard() • Set operations → union (|), intersection (&), difference (-) 🔹 Dictionaries – Key Learnings • A dictionary stores data in key-value pairs • Defined using {key: value} format • Keys must be unique and immutable • Values can be of any data type ✅ Operations practiced: • Accessing values using keys • Adding & updating elements • Removing elements → pop(), del() • Looping through keys, values, and items Thanks for our CEO G.R NARENDRA REDDY sir and Global Quest Technologies

𝗣𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝗨𝗽 𝗪𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 Python is a top choice for developers who work with algorithms and data structures. This is because Python is easy to use and has many libraries that make it perfect for machine learning and data science. You can use Python to optimize data processing, improve machine learning models, and make your work more efficient. Python's built-in data types, such as lists and dictionaries, help you build complex algorithms. Here are some key points to consider: - Sorting algorithms help you organize data and make it easier to retrieve information. - Mastering Python algorithms helps you create applications that perform well under different conditions. - Understanding how machine learning algorithms work helps you fine-tune models for better accuracy and performance. You can start by exploring the TheAlgorithms Python repository, picking an algorithm that interests you, and trying to implement it from scratch. Source: https://lnkd.in/e7v6bkq Optional learning community: https://lnkd.in/eheh7gk

🚀 Python Basics to Advanced Learning Series – Day 14 Today, I dived into one of the most important data structures in Python — Dictionaries. I explored how dictionaries work as key-value pairs, making data storage and retrieval efficient and structured. 🔍 Key Concepts I Learned: 🔹 Dictionaries store data in key → value format 🔹 Insertion order is preserved 🔹 Mutable data type (can be modified) 🔹 Supports heterogeneous data (both keys & values) 🔹 No indexing or slicing 🔹 Keys are unique, but values can be duplicated ⚙️ Operations I Practiced: ✅ Accessing values using keys ✅ Deleting elements using: del dict[key] dict.clear() del dict 🛠️ Built-in Functions Explored: dict(), len(), clear(), get(), pop(), popitem(), keys(), values(), items(), copy(), setdefault(), update() 💡 Dictionaries are extremely powerful when working with real-world data, APIs, and structured datasets. Grateful to Global Quest Technologies for the continuous guidance and support 🙏 Excited to keep learning and building every single day! 🔥 Keep Practicing. Keep Learning. Keep Growing. G.R NARENDRA REDDY #Python #PythonLearning #LearningJourney #Day14 #Dictionary #DataStructures #Coding #Programming #Developers #TechSkills #100DaysOfCode #SoftwareDevelopment #TechLearning #Developers #GlobalQuestTechnologies #PythonDeveloper #CodeNewbie

Unlock the power of data with our Data Analysis with Python course. This beginner-level, 12-hour instructor-led training is designed for learners who want to build practical data analysis skills using Python. The course covers essential tools and techniques used in real-world data analysis. What you will learn: • Working with Jupyter Notebook and setting up databases • Using NumPy for numerical computing • Data manipulation and analysis with Pandas • Sorting, ranking, and managing datasets • Data visualization using Matplotlib Available in both physical classroom and virtual sessions. Ideal for students, professionals, and anyone looking to develop practical data analysis skills with Python. View available dates and secure your seat today. https://lnkd.in/eRgGZEHe

Continuing My Python Journey: Working with Lists 🙌 Today’s learning was all about Python Lists, and it was a really insightful session! Under the guidance of Dr. Ankush Joshi, Isha Rajput, I explored how lists work as a mutable data type and how powerful they can be in programming. I learned various list operations and methods: ● Insertion operations – insert(), append(), extend() ● Deletion operations – clear(), remove(), pop(), del ● Slicing and iterating using for loops ● Creating matrices using nested lists Some key takeaways: ● append() adds elements at the end, while insert() places them at a specific index ● extend() helps combine lists ● pop() removes the last element by default ● del can delete elements or even the entire list 👌 Best part: Practice and clear explanations made the concepts easy to understand and apply. Grateful for such interactive learning and guidance Special thanks to: Dr. Gesu Thakur Dr. Ankush Joshi Isha Rajput Dr.Chinnaiyan Ramasubramanian #Python #Programming #CodingJourney #BCA #Learning #PythonBasics

🚀 Python Basics to Advanced Learning Series – Day 7 Today’s session was focused on one of the most important data structures in Python — Lists. This topic helped me understand how to store and manage multiple values efficiently. What I learned today: • What is a List and how it is used to store multiple values in a single variable • Lists are mutable, which means we can modify, add, or remove elements • How to create lists and access elements using indexing and slicing • Performing operations like adding, updating, and deleting elements • Understanding list traversal using loops • Learning important built-in functions used with lists: • Learning commonly used list methods: - "len()" → to find length of list - "append()" → add element at the end - "insert()" → add element at specific position - "remove()" → remove specific element - "pop()" → remove element using index - "clear()" → remove all elements - "sort()" → sort the list - "reverse()" → reverse the list - "count()" → count occurrences - "index()" → find position of element - "extend()" → add multiple elements • Practiced problems to understand how lists work in real scenarios This session helped me understand how powerful and flexible lists are in Python. Practicing different operations improved my confidence in handling data effectively. I’m learning all these concepts as part of my Python Basics to Advanced Learning Series at Global Quest Technologies Quest Technologies, and I’m improving step by step every day. Excited to learn more and build stronger concepts 🚀 G.R NARENDRA REDDY #Python #PythonProgramming #LearningJourney #Coding #Lists #DataStructures #ProblemSolving #SoftwareDevelopment #TechLearning #Developers #GlobalQuestTechnologies #GQT

🚀 Excited to share my latest blog! As a beginner in Python, I often felt confused about when to use lists, tuples, sets, or dictionaries So, I created a simple and practical guide: Choosing the Right Python Data Structure: A Beginner’s Decision Guide In this blog, I explained: ✔ Differences between list, tuple, set, and dictionary ✔ When to use each data structure ✔ Real-world examples for better understanding This helped me clearly understand how to select the right data structure instead of guessing. 🔗 Read my blog here: https://lnkd.in/dnBzV4VS Would love your feedback #Python #DataStructures #Programming #Beginners #Coding #LearningInPublic #Internship Innomatics Research Labs

🚀 Day 11: Python Lists.... Today’s session focused on continuation of Python Lists and exploring powerful operations: 🔹 Applied concatenation (+) and multiplication (*) on lists 🔹 Worked with comparison operators (==, !=) 🔹 Explored relational operators (>, >=, <, <=) 🔹 Practiced membership operators (in, not in) 📌 We also discussed nested lists and how to access elements within them. 💡 Learned about list comprehension – a concise and efficient way to create lists with simple syntax and examples. ✅ Key Takeaways: • Lists are dynamic (can grow/shrink) • Order is preserved • Duplicates are allowed • Supports positive & negative indexing • Lists are mutable • Can store heterogeneous data types This session helped me gain deeper insights into list. 🙏 Grateful to G.R NARENDRA REDDY Sir and Global Quest Technologies for their continuous support and guidance. #Python #FullStack #LearningJourney #Programming #Coding