Видео

I have recently completed this great course and am now seeking a job.

But chatgpt sometimes gives incorrect information

Thanks ❤❤❤❤

Sometimes Chat GPT is lag due to traffic. Other alternatives: Gemini, Grok, Copilot, etc. They're stunning as well and free

Thank you Monica for the video! Highly recommend taking these Python courses from Saylor Academy if you want a structured way to learn Python using ChatGPT. CS105: Introduction to Python CS250: Python for Data Science What you can do is for each Unit/Chapter that you are on, you can create a chat for that specific Unit that you are learning and you can copy and paste the contents for ChatGPT to summarize and make key points for you to study. Use the read aloud feature and set the language to your specifications for the model to read with better accuracy which will help the information to stick and easy to follow. With that I would also consider learning Java, and C++ and Building AI courses too! It will greatly expand your remote skills! 🙂

Excellent. I learnt a lot from your video

the cat

Great work! Easy and accessible to understand. But how to find part 1 you referred to? Link? Thanks for your edforts! 😊❤

Love it!!!!!!!!!!!

how long does it takes to learn completely and get a python job from your perspective? (Note: i am not starting from scratch, i got learn all basics of python).

Thank you very interesting video :)

This was a super excellent tutorial. I use ChatGPT in the same way to learn many different things. You have provided a great learning model.

Excellent content, thank you! Do you use PyCharm or VS Code? I'm thinking VS Code to use copilot, but I'm not sure if you can use chatgpt with Pycharm...

Beyond AI-900 I could not figure out what next course to take. Your review convinced me to sign up for the Machine Learning course at Coursera.

nooo moooonicaaa!!!!!!!!!!!!!!

Hey cna you please explain

ILove your channel it's full of value ✨

Hello ma'am, I had a few areas where I need guidance, I feel very lost, please help me 🙏 I’m Avi, currently pursuing a major in Mathematics and a minor in Economics at University of Delhi(India). Earlier this year(in beginning of my second semester) I realized that pure Mathematics might not offer the kind of applied opportunities I’m interested in. My country’s education system also presents challenges for someone aspiring to excel in core Mathematics. So, I decided to explore applications of Mathematics, which led me to Machine Learning. I really loved the core idea behind ML and decided to pursue it. I started learning with Python and ML fundamentals through a Udemy course(Krish Naik), completing three algorithms(linear regression with ridge lasso and elasticnet, Logistic regression, and decision trees) so far. My mathematical intuition has helped me dive into the subject with great intensity and I can proudly say my intuitions are very strong for all algorithms I've studied so far, but I now need some guidance to move forward. My questions are: Starting as an ML Engineer -What steps I must take to land my first internship as the competetion must be hugeee and my coding skills are not at par with my mathematical skills? My second year of college will end in six months. Transitioning to Data Science -I’ve learned that ML Engineering may not be an ideal first role for freshers. Data Science and Data Analytics seem like better starting points. However, my current course hasn’t covered much practical work in these areas. -How can I build strong analytical skills and develop meaningful projects? -What’s the best way to evaluate my understanding as I create these projects? Pathway to Gaming Companies -I aspire to work in gaming companies in roles like Project Head, Customer Analysis, Customer Behavior, or Retention Specialist. -What should my pathway look like to achieve this? -Is ML relevant to these roles? Should I also explore areas like Deep Learning, NLP, or others? Improving Technical Skills -Coming from a non-technical background, I lack foundational computing skills beyond ML and Data Science. How can I develop these essential skills? If possible I would like to connect with you and have a few other queries solved, i'm very scared of my future and everything feels like a burden, people on various platforms have been super pessimistic towards me and have claimed that ML bubble is supposedly going to burst soon Any advice or resources you share are greatly appreciated. Thankyou so much for your time in advance 😄 Best regards, Avi

Completely Agree

I definitely agree with the points you make. I did a couple of ML and Deep Learning Projects in the summer when I simultaneously was learning the ML concepts in the bootcamp. The bootcamp was focusing on the practical aspects of these algorithms and projects and did not care if we got the code from an other source, gpt stack overflow etc.. They only cared about the models that run without an issue. And I used mostly gpt code to get the certificate. That is why I feel short in the coding aspect, I cannot code anything without looking at the library sources on the web or use an LLM. I don't think this is an issue for me who is not working on the field and who is only a student. I feel like in 5 6 years the coding will be a tool that LLMs will perfectly provide and you will have to build the systems instead of writing syntax. Correct me if I am wrong about this and my self-coding experience please, anyone that has a say please do so that I can move properly. THX!! :)

i was a bit lost but i know my next step now thank you

Clickbait title got me

To some extent recruiters posting fake job offers on LinkedIn are definitely ones to blame 😂

Great video! It gave me a lot of insight into Fintech

I think in the future, AI will be a tool helping us in our daily tasks so what you did was only ahead of our times and will be considered normal in the near future perhaps

Great video! Thanks Monica

No you wasted your money. LOl. His course is a scam.

Good explanation Monica 👍

Congratulations.

How about engineer?🤔

the course that is on youtube is it the same one that is on coursera ?

first comment!! great video!!

This is Litterally the best advice I’ve received

I'm not going to lie it's pretty f****** easy for me to get a job. I go for the challenging stuff like plumbing and repair type work.

If dude applied to 735 jobs, then he is the problem.

Finding coding boring and having a degree in this field is like being a doctor when you are a misanthrope. Just shows how many got into this field because of money and the status.

it's easier to get a 🔫

I was doing IBM data science machine learning which was straight, easy and understandable structure but when I tried to go through stanford it was a bit difficult, although I am doing Master's Studies and have good continuous academic touch but stanford looks me complicated I don't know why. Instead of making difficult methodology there should be given priority to make people understood by making easy stuff.

Sounds like a project I'd get an F- 😂 Good explanation though!

Andrew Ng's course is one I recommend to students who struggle in some data science classes. As to the comments saying something like "it's too basic, you cannot land a job with this class": The point of Andrew Ng's class is to give a decent foundation and it does that really quite well. If you have a good foundation, you can build upon it with relative ease if and when you have to. If you don't, you'll struggle way more to acquire the skills later. And on top of this, you guys would be surprised to see how many "data science" jobs out there are relatively low-level in terms of required skills. Not every industry job will require you to know and use the latest and greatest modeling approaches. So it really depends on the sector and your role.

Got curious on this, does it teach you on how to build recommendation systems for example ?

No way it can land some one a job in 2024, this course is too basic

Thanks I am also taking this course and I completely agree with you - from on India

amazing ❤

Nice work Monica, here are some of my thoughts on your work: - The implementation of correlation in numpy is Pearson correlation and as you may know it measures the "linear association" of a pair of "continuous variables" which is not a correct measure of correlation between your target variable (continuous) and gender (binary). Instead you should use Point-Biserial Correlation. - Pearson correlation assumes normally distributed continuous variables which is not the case for the majority of independent variables. Additionally, Pearson correlation is affected by outliers if you take a look at formula so ideally you need to perform additional analysis to detect outliers in your data and decide what to do with it (remove/winsorize/scale). - All the algorithm you used in your project are intended to capture non-linear relationship between target and explanatory variables, not sure of the choice of Pearson correlation since it is a measure of linear association. Spearman rank correlation is a better candidate for non linear association measure since it captures monotonic relationships. - You can still keep the gender by encoding (one hot encoding) the variable (for random forest and AdaBoost) or converting the values of it into 2 dummy variables as for the case of polynomial regression, provided that there is a strong association between target variable and gender from point biserial test. - What is the point of checking for the normality of distribution of explanatory variables when you used models which do not strictly require normally distributed variables? - You can have correlated variables (not to the extreme of 0.9+) as final selected features since all the algorithms that you use have regularization to control for multicollinearity. - Polynomial regression model is sensitive to outliers, you probably need to have some sorts of treatment for outliers. - Since polynomial regression is a parametric model, it relies on several assumptions such as Independence of Errors, Homoscedasticity of the residual variance. Normality of Residuals, etc. I think this is something you can check cus if these assumptions do not hold, the results aren't statiscally reliable.

I was trying to find someone going through a deep review like this! I’m a current CS student and wanted to reinforce some of the topics I’ve learned already. Thank you so much! Can’t wait to start!

Quite interesting!! I'll be very grateful if you can provide me some guidance as I'm ultra pro Max beginner. 😭

Thank you for making this video! I just started this course. Hoping it will help me for getting ml role 😅

What kind of models are you working with at work?

How you landed the job . The course only covers basics of ML