Knowing Python is valuable, but SQL serves a different purpose.

SQL (Structured Query Language) is used for managing and querying databases, while Python is a general-purpose programming language.

If you work with databases or data analysis, learning SQL can be very beneficial to manipulate and retrieve data efficiently.

Generally, SQL is optional for my students. In fact, it's a separate class all together as what the student may intend doing with python may not require working with database.

If you intend developing web applications with python, I suggest you learn SQL.

If you're just starting out with python programming, I have a gift for you. It's a 30 Days Python study plan. It's absolutely FREE. Specifically designed to make learning python programming less overwhelming.

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SQL complements your Python skills and can help you work more effectively with databases.

Tech Tips For Today:
Avoid using your birth details for password. It's the easiest to crack.

Building a portfolio as a tech professional showcases your skills, projects, and expertise to potential employers or clients.

It provides tangible evidence of your abilities, helping you stand out in a competitive field.

A portfolio can demonstrate your problem-solving skills, creativity, and experience with various technologies.

It also provides a way for you to track your progress and growth over time. Having a strong portfolio can make it easier to land job interviews, contract opportunities, or freelance work.

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Building an impressive portfolio as a beginner Python programmer involves showcasing your skills and projects effectively. Here's a step-by-step guide:

✓Choose Your Projects: Select projects that interest you and align with your goals. Aim for a mix of complexity to demonstrate various skills.

✓Start Simple: Begin with small projects to learn the basics. Simple web scrapers, to-do lists, or calculator apps are good starting points.

✓Open Source Contributions: Contribute to open-source projects on platforms like GitHub. It demonstrates collaboration, version control, and real-world coding.

✓Personal Website: Create a personal website showcasing your portfolio, projects, and a brief bio. It's a great way to stand out.

✓GitHub: Create a GitHub repository for each project. Include clear README files with project descriptions, setup instructions, screenshots, and a link to the live version if applicable.

✓Diverse Projects: Include projects that cover different areas like web development, data analysis, automation, etc. This shows versatility.

✓Document Your Code: Write clean, well-documented code. Use comments to explain complex sections and include docstrings for functions.

✓Version Control: Use Git for version control. It shows your ability to work on a team and manage code changes effectively.

✓Showcase Problem Solving: Include projects that solve real-world problems or automate tasks. Explain the problem, your solution, and how your code addresses it.

✓Quality over Quantity: Focus on quality projects rather than the quantity. A few well-executed projects are more impressive than many half-finished ones.

✓Personal Touch: Add your unique touch to projects, whether it's through design, functionality, or innovative features.

✓Learning Process: Document your learning journey. Show how you tackled challenges, learned from mistakes, and improved over time.

✓Collaboration: If you've collaborated with others, highlight teamwork skills and how you coordinated efforts using tools like Git.

✓Continuous Learning: Keep updating your portfolio as you learn new skills and complete more projects. This shows growth and dedication.

✓Online Presence: Share your projects on platforms like LinkedIn, Twitter, and relevant programming forums to get feedback and connect with others in the community.

✓Practice Algorithms and Data Structures: If you're interested in software development, demonstrate your understanding of algorithms and data structures through coding challenges or projects.

Remember, an impressive portfolio isn't just about showcasing technical skills. It's about showing your problem-solving abilities, your passion for coding, and your willingness to learn and improve.

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Join our telegram python course and mentorship

OgogoroFreak:
It actually a matter of positioning and time.

In that case, one must experiment with different time of the day to see when works best.

So far, I haven't seen frequency of posting making any difference. Maybe I missed it though.

Thanks og²oroFreak for the heads-up. I think I know where to start experimenting.

Does anyone has any ideas how the nairaland algorithms work especially as regards getting views for a post?

Please be kind to share. Thanks a bunch.

The time it takes to learn Python programming in Nigeria, or anywhere else, can vary depending on factors such as your prior programming experience, the amount of time you can dedicate to learning, and your learning pace.

Generally, it might take a few months to gain a solid understanding of Python basics and start building simple projects.

Let me establish at this point that python is about the easiest programming language to learn.

Little wonders some secondary schools in Nigeria are adopting it as the go programming language for their students.

Having said that, it's also important to state that just understanding how a programming language works doesn't necessarily make you a programmer.

Being a programmer goes way beyond writing codes. There is the logic part and the algorithms and all the data structures.

That been said, understanding the syntax of python, and grasping concepts as variables, down to file handling, could take anytime between 6 to 8 weeks.

However, mastering the language and its advanced concepts could take a year or more of consistent practice and learning.

The truth is, you can never finish learning. But with discipline, dedication and good practice, + joining a great community of learners, you should be ready to land your first job or launch your first app in 6 months.

The secret is hands-on course + mentorships.

And yes, the best time to start your programming journey is now.

kindly follow me on Twitter @thetechbroh

No doubts this is the most popular topic among people who are new or intending to go into the tech/programming space. Sometimes it even become an argument rather than a discussion. But then, really, what is the best programming language for a beginner to learn?

The simple and short answer is, "it depends", yap. It depends on your interest. Again, this is a mistake both old and new programmers make. You don't just say I want to be a programmer. It is too generic and you won't go far with such mindset. I lived in this error for long and didn't have much to show till I changed my mindset. Be specific.

Say something like "I want to be a mobile app programmer", or an "AI Programmer", "Web programmer", "Crypto programmer" etc. You get the point now. Yes, whatever you do, you are still a "programmer". But it is in your best interest to be specific.

Different tasks are done with different programming languages. You see why it "depends", and why you can't say that the best programming language to learn is this or that. There are programming languages best suited for Machine Learning, IOS Apps, Web Apps, NFT, Crypto, Robotics, AI, Data Science, Cyber Security, etc.

In the following days, I will be making posts covering the best programming languages for different fields of software development and engineering. I will kindly ask you to follow me and share my posts to benefit more folks. Thanks.
I will also be grateful if you add value to this post by commenting to strengthen a point I made, or point out an error in the post. You are the real MVP .

The Tech Broh.

Python
The most popular programming language for data science nowadays is Python. It is a straightforward, open-source language that has been used since 1991. This dynamic, all-purpose language is by nature object-oriented. Additionally, it supports a variety of programming paradigms, including functional, structured, and procedural.

As a result, it is also one of the most widely used languages for data science. It is quicker and a better alternative for data transformations with fewer than 1000 iterations. With the help of the Python packages, natural data processing and data learning become simple tasks. Additionally, Python creates a CSV output that makes it simpler for programmers to interpret the data in a spreadsheet.

Other great choices for data science include:
Javascript
R
Scala
SQL
Julia

Python developer roles are in high demand, as many major companies — including DropBox, Netflix, and Facebook — use it.

Python developer jobs are also comparatively lucrative. According to Indeed*, Python developers earn an average salary of $108,391, which makes it the fourth-most lucrative programming language behind Ruby ($120,174), C++ ($114,000), and JavaScript ($111,623).

Python developers also have the opportunity to earn a high salary with less experience, according to StackOverflow.

Python is easy to learn. You can use it for both small and complex tasks, and it is used across many different industries — from its more common applications in data science and software engineering to environments like mobile app development, artificial intelligence, and machine learning.

This multifaceted use is due to the wide array of Python libraries available (over 125,000, to be specific). Libraries are collections of pre-written code in a particular language that anyone can access.

For self employment, those who want to be their own boss, there are lots of simple but powerful personal projects you could take on with just a basic understanding of python. Example of projects is building bots for almost anything.