#complete machine learning course with python

22 from the ask game: What do you want to be when you grow up?

Oh god… Well, I myself am still figuring out what I want to be and am trying to explain it to myself. There are some things that I would like to do in my life, but as for a job, I don’t know. Sometimes, I think about how it’d be cool to be in a court-room and be a lawyer and be involved in criminal investigations like Legally Blonde, Sherlock, or High Potential. I have been taking a Journalism course and Speech and Debate (the high school I have been waitlisted on has a REALLY good Speech and debate team and a lot of the alumni from that class go to Harvard or UCLA). But, I have been told that lawyers are at risk of AI influencing how their jobs are done, and I’ve been warned lawyers can conduct some nasty business for the sake of earning a high salary. I do have an interest in computer science… Specifically neural networks and machine learning models. I kind of yapped about those in a TADC theory docs I made… I did get into AI and machine learning because of TADC, I really like AI too.

I’ve been taking some computer science classes and Python. But, there are some other things I’d like to do. Things I want to complete in my life, but I don't know about it being a full-blown career path or a job.

Looking through my to-do lists this month, I'm realizing that part of the reason why I'm not able to cross things off my list so easily is because the points I add to my list are fairly ambiguous and don't have a clear finish point. For instance, when I would write "learn binary trees on Python"; well what does that mean? Having actual actionable and completable items on my to-do list helps to better set daily goals for myself as well as to actually complete those goals. It often get intimidated seeing such large tasks that I didn't know how to approach so breaking those down for myself has made a world's difference. Yes, yes I'm a yapper.

Machine learning technology has truly transformed multiple industries and continues to hold enormous potential for future development. If you're considering incorporating machine learning into your business or are simply eager to learn more about this transformative field, seeking advice from experts or enrolling in specialized courses is a wise step. For instance, the ACTE Institute offers comprehensive machine learning training programs that equip you with the knowledge and skills necessary for success in this rapidly evolving industry. Recognizing the potential of machine learning can unlock numerous avenues for data analysis, automation, and informed decision-making.

Now, let me share my successful journey in machine learning, which I believe can benefit everyone. These 10 steps have proven to be incredibly effective in helping me become a proficient machine learning practitioner:

Step 1: Understand the Basics

Develop a strong grasp of fundamental mathematics, particularly linear algebra, calculus, and statistics.

Learn a programming language like Python, which is widely used in machine learning and provides a variety of useful libraries.

Step 2: Learn Machine Learning Concepts

Enroll in online courses from reputable platforms like Coursera, edX, and Udemy. Notably, the ACTE machine learning course is a stellar choice, offering comprehensive education, job placement, and certification.

Supplement your learning with authoritative books such as "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron and "Pattern Recognition and Machine Learning" by Christopher Bishop.

Step 3: Hands-On Practice:

Dive into real-world projects using both simple and complex datasets. Practical experience is invaluable for gaining proficiency.

Participate in machine learning competitions on platforms like Kaggle to challenge yourself and learn from peers.

Step 4: Explore Advanced Topics

Delve into deep learning, a critical subset of machine learning that focuses on neural networks. Online resources like the Deep Learning Specialisation on Coursera are incredibly informative.

For those intrigued by language-related applications, explore Natural Language Processing (NLP) using resources like the "Natural Language Processing with Python" book by Steven Bird and Ewan Klein.

Step 5: Learn from the Community

Engage with online communities such as Reddit's r/Machine Learning and Stack Overflow. Participate in discussions, seek answers to queries, and absorb insights from others' experiences.

Follow machine learning blogs and podcasts to stay updated on the latest advancements, case studies, and best practices.

Step 6: Implement Advanced Projects

Challenge yourself with intricate projects that stretch your skills. This might involve tasks like image recognition, building recommendation systems, or even crafting your own AI-powered application.

Step 7: Stay updated

Stay current by reading research papers from renowned conferences like NeurIPS, ICML, and CVPR to stay on top of cutting-edge techniques.

Consider advanced online courses that delve into specialized topics such as reinforcement learning and generative adversarial networks (GANs).

Step 8: Build a Portfolio

Showcase your completed projects on GitHub to demonstrate your expertise to potential employers or collaborators.

Step 9: Network and Explore Career Opportunities

Attend conferences, workshops, and meetups to network with industry professionals and stay connected with the latest trends.

Explore job opportunities in data science and machine learning, leveraging your portfolio and projects to stand out during interviews.

Welcome to our comprehensive Selenium course designed to help individuals from all backgrounds, whether novice or experienced, enhance their automated testing skills and become proficient in Selenium. In this article, we will delve into the world of Selenium, an open-source automated testing framework that has revolutionized software testing. With our course, we aim to empower aspiring professionals with the knowledge and techniques necessary to excel in the field of automated testing.

Why Choose Selenium?

Selenium offers a wide array of features and capabilities that make it the go-to choice for automated testing in the IT industry.

It allows testers to write test scripts in multiple programming languages, including Java, Python, C#, and more, ensuring flexibility and compatibility with various project requirements.

Selenium’s compatibility with different web browsers such as Chrome, Firefox, Safari, and Internet Explorer makes it a versatile choice for testing web applications.

The ability to leverage Selenium WebDriver, which provides a simple and powerful API, allows for seamless interaction with web elements, making automating tasks easier than ever before.

Selenium’s Key Components:

Selenium IDE:

Selenium Integrated Development Environment (IDE) is a Firefox plugin primarily used for recording and playing back test cases. It offers a user-friendly interface, allowing even non-programmers to create basic tests effortlessly.

Although Selenium IDE is a valuable tool for beginners, our course primarily focuses on Selenium WebDriver due to its advanced capabilities and wider scope.

Selenium WebDriver:

Selenium WebDriver is the most critical component of the Selenium framework. It provides a programming interface to interact with web elements and perform actions programmatically.

WebDriver’s functionality extends beyond just browser automation; it also enables testers to handle alerts, pop-ups, frames, and handle various other web application interactions.

Our Selenium course places significant emphasis on WebDriver, equipping learners with the skills to automate complex test scenarios efficiently.

Selenium Grid:

Selenium Grid empowers testers by allowing them to execute tests on multiple machines and browsers simultaneously, making it an essential component for testing scalability and cross-browser compatibility.

Through our Selenium course, you’ll gain a deep understanding of Selenium Grid and learn how to harness its capabilities effectively.

The Benefits of Our Selenium Course

Comprehensive Curriculum: Our course is designed to cover everything from the fundamentals of automated testing to advanced techniques in Selenium, ensuring learners receive a well-rounded education.

Hands-on Experience: Practical exercises and real-world examples are incorporated to provide learners with the opportunity to apply their knowledge in a realistic setting.

Expert Instruction: You’ll be guided by experienced instructors who have a profound understanding of Selenium and its application in the industry, ensuring you receive the best possible education.

Flexibility: Our course offers flexible learning options, allowing you to study at your own pace and convenience, ensuring a stress-free learning experience.

Industry Recognition: Completion of our Selenium course will provide you with a valuable certification recognized by employers worldwide, enhancing your career prospects within the IT industry.

Who Should Enroll?

Novice Testers: If you’re new to the world of automated testing and aspire to become proficient in Selenium, our course is designed specifically for you. We’ll lay a strong foundation and gradually guide you towards becoming a pro in Selenium automation.

Experienced Testers: Even if you already have experience in automated testing, our course will help you enhance your skills and keep up with the latest trends and best practices in Selenium.

IT Professionals: Individuals working in the IT industry, such as developers or quality assurance engineers, who want to broaden their skillset and optimize their testing processes, will greatly benefit from our Selenium course.

You dont need to make a quality art to love drawing. If drawing realistic and high quality is your main goal, then it will take pretty long and you need to resist.

But like i said! Quality of a drawing shouldnt be how you can have fun while drawing. The way you can love to draw, is being able to draw something you desire to draw. If you desire something like tall building on a detailed night time with street lights reflection and moon on the sky with clouds raining 1920x1080 scenery , that.. wont work out well, if you are inexperienced.

The harsh truth is, we cant just "bam, done" our way out espacially when it comes to drawing something. Sometimes, for quality work, we need more than practice.

Now i obviosuly am just a doodler and not a professional, but i can give few tips to help you and others who desire high quality work and for those who are unsure how to love making art!

Research, And Study Art

High quality works requires their respect. You need to research and study the art topic of your mission.

For example, you want to draw humans? You need to take a look at anatomy.

In today's internet and technology, the information you want can easily be accessed.

Be Stubborn A Little

Do not ever give up if you truly want to love drawing. Be stubborn, and dont let go easily. But of course, this is only IF you are SURE you want to learn and love drawing.

Love cannot be forced.

Make It Interesting

Now, if the topic you want to draw is not interesting, it may bore you and you'd think drawing is no fun.

Drawing OF COURSE ISNT fun if you dont carefully choose your topics!! For example, i myself always find normal human drawings a bit boring. Sure, i would respect if it is highly detailed and all. But if someone draws a regular ass human portrait, with not even a pose, uh.. thats a bit boring? What am i supposed to do w that? I see humans all of time. It just looks regular, and not interesting to me.

However. If someone shows me some crazy shit about i dunno a war art of tanky robots taking over a castle with dragons fucking flying in the air or something they just drawed, and even if its low quality, THEN I WOULD GO "OOH THE FUCK IS THAT."

You even may notice it on my works as well! I oftenly do memes or overall stupid silly stuff! For me, i cant just draw Niko standing in there. No. I NEED to add something stupid. Like a banana costume. Maybe TWM in the back making a nuclear bomb with a horrific smile. Or just Niko but with some silly pose.

The point is! You should use your imagination and add elements to your art that interests you!

What is interesting to you? Or your hobbies? Try adding them to your art! And not for the sake of high quality, remember! To love drawing, you first need to have fun with it.

Challenge Yourself

Yes. Challenging yourself on ANYTHING can dramatically improve you.

For example i challenged myself to learn Python last year. I was like "if i dont learn more coding language i am going to die"

Okay maybe you dont need to be that harsh

Another example is me challenging myself to install Arch Linux with text to speech screen while i blindfold myself.

I know, sounds insane and looks pointless. But that stupid decision made me actually fucking learn Linux, virtual machines and bash language more.

Sometimes, all starts with an challenge. My last example is me starting to learn how to play flute just because i thought i should play sans music in a flute while walking around.

Okay my last LAST example : I challenged myself to draw Niko's hat accurately, months ago. Which was incredibly hard but it DID improved me how i draw their hat today!

Challenge yourself, but in a fun way! Dont quickly lose hope and get angry if you cant complete the challenge you just decided to do. You WILL complete it. Once you decide to, its over. It only takes time.

I can suggest daily stuff like Inktober Challenge too! I always wanted to do that!

Different Styles

Like i said previously, never try to draw the same thing in a same way. The result will not change in that way and you'll be exhausted.

Try different brushes, colors, style, objects etc.! Sometimes, draw something completely unrelated to you! Yeah, fr!

Friends Are Good. Artist Friends Are Even Better

If you are lucky and have art buddies, oohh DONT WASTE TIME. Draw with them!

I have bunch of art buddies that i draw with, mostly with online ways like aggie.com , skribbl.io , Gartic Phone etc! I can not explain enough how fun and important these moments are!

If you dont have artist friends, its actually easy to find! Like me, being in a fandom and making art for it is mostly enough to have interacting with other artists in the community!

They comment on your work, you comment on their work! You then talk other stuff besides art with them too, and in time, bam! Friens!

That's how it went for me! Amazing artists in OneShot community (also from other communities!!) reached me out, and so i reached them out too!

How? Drawing, of course :> when i draw Niko, other fellow Niko enjoyers found me, and so did i found them!

And i admit, i feel like a little bug sometimes when i compare my works and some of my artist friends work. Some of them are really born to draw, oh i can say! Me, not really am just vibing!

But this also helped me. Because, well, if someone is good at something and they see no problem teaching it to you too.. YOU ARE BLESSED!

Anyways this also went kinda long sorry

App Academy Open

In signing up for App Academy Open, you’ll access more than 1,500 hours of completely-free curriculum that includes machine learning, data science, data structures, computer programming languages, and building frameworks for iOS and Android mobile apps — as well as how to apply these skills, step-by-step, in real-world applications. And if you’d like additional support, you’ll also have the option of utilizing the $29.99/month mentorship program for features such as an instructor-led chatroom with the opportunity to work alongside other App Academy Open students!

Visit App Academy Open

Codecademy

Codecademy is a popular platform for beginning a coding journey. You can start from square one, or you can evaluate your skills to find the level that suits you the best. And their instant-testing of coding skills (including HTML & CSS, JavaScript, PHP, Python, Ruby, Angularjs, The Command Line, and more) allows you to learn and practice in real-time to make sure you’re understanding concepts correctly.

Visit Codecademy

freeCodeCamp

freeCodeCamp.org is a nonprofit that offers around 3,000 hours of coding curriculum, but they also go beyond that. Once you’ve finished learning to code, they’ll give you the opportunity to work on projects for other nonprofits. This way, you’ll get hands-on, real-world experience while earning your free certification.

Visit freeCodeCamp

Khan Academy

Like freeCodeCamp, Khan Academy is also a nonprofit — however, rather than focusing on tech, they instead offer a wide range of programs. While their selection of coding classes may not be as robust as other platforms, they are a great place for beginners and even provide courses for young children, to begin building their skills early!

Visit Khan Academy

Coursera

Coursera also opts not only to offer courses in which to learn to code, but also a range of programs provided through other colleges, universities, and companies. Although, while there are several free courses available in addition to paid, any certifications would only be accessible through their paid options.

Visit Coursera

Udemy

Similar to Coursera and Khan Academy, Udemy offers courses covering a variety of topics, which includes a section on coding. And although most of their courses are paid (costing roughly $20–$200 each), they do have some free options available as well — although you’ll only be able to view the video content. Any certifications or instructor interactions are only included in their paid programs. Additionally, you’ll want to make sure to check star ratings, reviews, and instructor credentials, since anyone can add a class to Udemy’s site!

Use git!!!!! Use git from the start for all of your programming projects, and probably also for everything else! I was using fucking google drive to sync my work between my laptop and desktop for the first few semesters of college and it fucking sucked! If you don't already know how to use git, learn it now or very soon, cuz there will probably be later classes that require it and it'll be so incredibly useful to already know how to use it! Also if you're not comfy putting your coursework on like github or gitlab, go check out Keybase, there's free private git repo storage in there, it's neat

Anyway, as far as like actual coursework or general CS knowledge that'll be useful? I feel like that's highly dependent on the particular program you're in tbh. Like if you were going to my alma mater, (doubtful, it's in upstate New York and you say "university" instead of "college" so I assume you're in the UK or otherwise non-American,) I'd give you all sorts of advice about specifically the Data Structures course, which is the course after CS 1 that's notorious for the sheer difficulty of its assignments and tests. We used C++ there. I hear many other programs have data structures courses taught in Java or Python that are just a complete walk in the park. So who knows!

That said, something that was very generally useful for me was to come in with a more-or-less solid understanding of how code is actually executed in hardware, how assembly/machine code works and how higher-level languages map to it. I spent the summer before my freshman year working through Hacking: The Art of Exploitation by Jon Erickson, so I was comfy writing low-level C and using a debugger, and had a pretty decent understanding of how software could fail. That was all tremendously helpful. (Also that book fucks really hard and you should definitely give it a look at some point in the future!)

On the more theoretical side of things, I think you might already be ahead of my freshman self! Certainly you already know Haskell, with which I wasn't acquainted until like my fourth or fifth semester as part of the programming languages course. If you're not already familiar with the concepts of formal systems/languages/syntax and computability/decidability, maybe give Gödel Escher Bach a read (or at least the first few chapters where he introduces all that stuff). I think that was the most generally useful theoretical knowledge I had going in. Certainly that was about half of the subject matter of my introductory Foundations of Computer Science course (the other half being combinatorics and finite automata/Turing machines).