🔟 Python resources to boost your resume in 2023

𝟭. 𝗜𝗻𝘁𝗿𝗼 𝘁𝗼 𝗣𝘆𝘁𝗵𝗼𝗻
This a great course to get started with learning Python, if you have no coding experience.
👉 https://kaggle.com/learn/intro-to-programming

𝟮. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗰𝗼𝘂𝗿𝘀𝗲
Learn the fundamentals like functions, loops, conditional statements, etc of the most important language for data science.
👉 https://kaggle.com/learn/python

𝟯. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀 𝗶𝗻 𝗣𝘆𝘁𝗵𝗼𝗻
Part 1 prepares you for PCEP – Certified Entry-Level Python Programmer Certification.
Part 2 prepares you for PCAP – Certified Associate in Python Programming Certification.
👉 https://netacad.com/courses/programming/pcap-programming-essentials-python

𝟰. Python Data Structure and Algorithms
👉 https://t.me/programming_guide/76

𝟱. 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
You'll learn Python fundamentals like variables, loops, conditionals, and functions.
Then you'll quickly ramp up to complex data structures, networking, relational databases, and data visualization.
👉 https://freecodecamp.org/learn/scientific-computing-with-python/

𝟲. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
You'll learn how to read data from sources like CSVs and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.
👉 https://freecodecamp.org/learn/data-analysis-with-python/

𝟳. 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
You will learn how to implement the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general.
👉 https://cognitiveclass.ai/courses/data-visualization-python#about-course

𝟴. 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
You will build several neural networks and explore more advanced techniques like natural language processing and reinforcement learning.
👉 https://freecodecamp.org/learn/machine-learning-with-python/

9. Practice Python
👉 https://learnpython.org/

10. Free Python course by datacamp
👉 https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=1

ENJOY LEARNING 👍👍

Essential Tools, Frameworks, & Concepts in Java Programming

1. Core Java Concepts:

Object-Oriented Programming (OOP)

Exception Handling

Multithreading

Collections Framework

Generics

Java I/O (Input/Output)

Lambda Expressions and Streams (Java 8 and beyond)


2. Java Frameworks:

Spring Framework: Comprehensive framework for enterprise applications.

Hibernate: ORM (Object Relational Mapping) framework.

Apache Struts: For building web applications.

Play Framework: Lightweight and reactive web application framework.


3. Build Tools:

Maven

Gradle


4. Java Testing Frameworks:

JUnit

TestNG


5. Web Development with Java:

Servlets and JSP (Java Server Pages)

Spring MVC

Thymeleaf


6. Java for Microservices:

Spring Boot

Spring Cloud

Quarkus


7. Database Integration:

JDBC (Java Database Connectivity)

JPA (Java Persistence API)


8. IDEs for Java Development:

IntelliJ IDEA

Eclipse

NetBeans


9. Advanced Concepts:

JVM (Java Virtual Machine) Internals

Garbage Collection

Memory Management

Reflection API


10. Java for Cloud and Distributed Systems:

Apache Kafka

Apache Hadoop

Kubernetes (with Java apps)


11. Networking in Java:

Sockets and ServerSockets

RMI (Remote Method Invocation)


12. Popular Java Libraries:

Apache Commons

Google Guava

Jackson (for JSON parsing)


13. Java for Android Development:

Android Studio

Java SDK


Free books and courses to learn Java👇👇

https://imp.i115008.net/QOz50M

https://bit.ly/3hbu3Dg

https://imp.i115008.net/Jrjo1R

https://bit.ly/3BSHP5S

https://t.me/Java_Programming_Notes

https://introcs.cs.princeton.edu/java/11cheatsheet/

Join @free4unow_backup for more free courses

ENJOY LEARNING👍👍

Soft skills questions will be part of your next data job interview!

Here is what you should prepare for:

1. 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Be ready to discuss how you explain complex data insights to non-technical stakeholders.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“How do you ensure that your data insights are understood and get used by non-technical stakeholders?”

2. 𝗧𝗲𝗮𝗺 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Show your ability to work well with others.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“Can you talk about a time when you had to manage a conflict within a team? How did you resolve it?”

3. 𝗣𝗿𝗼𝗯𝗹𝗲𝗺-𝗦𝗼𝗹𝘃𝗶𝗻𝗴: Highlight your critical thinking and problem-solving skills.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“Describe a situation where you had to make a quick decision based on incomplete data. What was the outcome?”

4. 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Demonstrate your flexibility and openness to change.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“How do you handle sudden changes in project priorities or scope?”

5. 𝗧𝗶𝗺𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Prove your ability to manage multiple tasks and deadlines.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“Tell me about a time when you were under tight deadlines. How did you manage to meet them?”

6. 𝗘𝗺𝗽𝗮𝘁𝗵𝘆 𝗮𝗻𝗱 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: Show your ability to understand stakeholder needs.

𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯:
“How do you approach understanding the needs of different stakeholders when starting a new project?”


Structure your answers using the STAR method (Situation, Task, Action, Result). This helps you provide clear and concise responses that highlight your skills.

By preparing for these soft skills questions, you’ll demonstrate that you’re not just technically fit, but also a well-rounded professional ready to make an impact on the business.

You can find useful tips to improve your soft skills here: 👇 https://t.me/englishlearnerspro/