Python for Data Science and Machine Learning Bootcamp
Are you ready to start your path to becoming a Data Scientist.
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms.
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed. Data Science is a rewarding career that allows you to solve some of the world's most interesting problems.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science.
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost. With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy.
We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python. Here a just a few of the topics we will be learning:
- Programming with Python
- NumPy with Python
- Using pandas Data Frames to solve complex tasks
- Use pandas to handle Excel Files
- Web scraping with python
- Connect Python to SQL
- Use matplotlib and seaborn for data visualizations
- Use plotly for interactive visualizations
- Machine Learning with SciKit Learn, including:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Decision Trees
- Random Forests
- Natural Language Processing
- Neural Nets and Deep Learning
- Support Vector Machines
- and much, much more.
Enroll in the course and become a data scientist today.
Get a Reminder
Rating | 4.5★ based on 7,216 ratings |
---|---|
Length | 25 total hours |
Starts | On Demand (Start anytime) |
Cost | $12 |
From | Udemy |
Instructors | Jose Portilla, Pierian Data International by Jose Portilla |
Download Videos | Only via the Udemy mobile app |
Language | English |
Subjects | Data Science Business |
Tags | Data Science Business Development Data & Analytics |
Get a Reminder
Similar Courses
What people are saying
step by step
Easy to follow step by step as is is well structured.
Finally, found a course that takes me step by step through all popular libraries, methods and types regarding ML.
KNN, K-Means, Decision Trees and random Forrest) without being shown what is actually been done, step by step in code.
Amazing course, giving a step by step learning experience on Machine Learning.
His voice is just on a screen, but I feel like I'm in class listening to him teach step by step.
The explanation is very clear and done with a step by step pace useful for beginners Very good!
Very informative examples + Exercises for practice = Great learning experience indeed very good....totally worth getting overview and detailed step by step explanation I think this program has GREAT value!
For the cost, there is SO much information and walking me though it step by step is so useful.
Simple and clear, good for novice Best course for revision... Great python overview and how to apply it to data science in a clear step by step manner.
Nice step by step Very clear and the pace is fast enough it is very easy to understand concise and easy to understand.
Upto know its very good Easy to follow Great for the beginner clear and helpful Step by step instructions are appreciated.
Step by step explanation for real world application.
He takes each topic step by step and calls out important functions.
Jose has built this course step by step in a progressive manner, which is very easy to understand for any one.
Read more
neural networks
loved it totally Expected more in neural networks contents, as for the rest, pretty good.
He walks through the background knowledge you need to learn machine learning, then through many common models that are used in practice, all the way up to deep neural networks.
This course was an amazing introduction to Python for Machine Learning, Neural Networks, etc., however there is some (little) room for improvement (more on that later).
It would be helpful to have a deeper discussion of theory, especially in the neural networks section.
Ultimately, I feel considerably confident in MLA and have a basic grasp of how to utilize Sparks and neural networks For anyone who has done Jose's other course on R with Machine Learning, this course should be very familar.
Only draw back was the seriously long and complicated installation process for both Sparks and neural networks, and there being no additional ebooks to read up on.
Totally worth it if you're looking for an introduction to ML and Neural Networks with Python.
-- the tensorflow.contrib.learn is a neat and easy way to implement neural networks but apparently it changes all the time!
I think a complete newbie to ML would find it difficult to understand the material especially the neural networks section.
The Tensorflow library used for neural networks is evolving so fast that neither the original lecture nor (as of late June 2017) even the corrections correspond well to the current APIs.
Training material is great, as an medium/advanced R analyst with zero background in Python I found the lectures and the Jupyter Notebooks as a great knowledge aid, the topics included in the course start from the basic until the more advanced stuff such as Machine Learning and Deep Neural Networks.
Generally, I believe it's a good introduction to Python in Data Science, including many data analysis tools, even the most recent innovations like Deep Neural Networks.
All the content is good and clear, but you won't see much about neural networks.
If you could have added more applications on neural networks frameworks tensorflow, keras etc .
Read more
tensor flow
I recommend updating the Tensor Flow MNIST videos to the current Python 3.7 and tensorflow 2.0 as I had several issues to install tensorflow 1.10, and eventually didn't manage to practise those two related videos completely.
(Wanted to but didn't reduce to 4 stars right at the end since the entire Tensor Flow section at the end seems to be out of date without documentation on how to follow along) Yeah it is a great course to take if you are a beginner The Instructor should more Focus in the theory part.The coding part was relatively good for beginners but the theory part was less.
The neural networks exercise solution has become outdated and does not work due to changes in Tensor Flow.
In special, the module regarding Tensor Flow is really poor, without even mentioning basic concepts such as cost functions or back-propagation.
I did the whole course to build up intuition for Deep Learning / Tensor Flow, but that section was a bit frustrating.
Informacje o Tensor Flow i Spark były nieaktualne.
The Tensor Flow part was confusing.
not explained well the concepts of tensor flow how really it does work , focused on syntax but wanted to know concepts This was a great foundational course for almost all branches of further advanced data science work.
The topics of natural language processing and deep learning with the tensor flow are vast and the course sections were merely an introduction to the basics.
Also, the course touches on some advanced libraries like tensor flow for neural networks and using pyspark which is very good.
It was great experience going through the, I think I will need more time with tensor flow.
Some of the tensor flow examples need updating to reflect the latest tensor flow API.
However, the last section about tensor flow is a little bit rush.
Also, it is nice that the course goes from "This is what a dictionary is" all the way to Tensor Flow.
Read more
complete python bootcamp
I took his course "Complete Python Bootcamp" earlier and really liked the delivery style.
it was great.. i have taken complete python bootcamp also so i am finding it quite understandable as i have already learnt python from jose portilla sir it was a great experience..thankyou sir great course with all necessary information to start in Machine learning Overall a very good course.
The Jupyter notebooks are not as clear as the ones for Complete Python Bootcamp.
I've taken the Complete Python Bootcamp from Jose Portilla before and this course builds very well further on that one.
Simple and effective I have already taken the author's Complete Python Bootcamp series and was very satisfied.
I have completed Jose's 'Complete Python Bootcamp' course previously and enjoy the teaching style and use of Jupyter Notebooks so i'm looking forward to get deeper into the content.
Thanks some problems running jupyter notebooks on windows 10 the anaconda prompt works tho I have taken the Complete Python Bootcamp course from Jose and I really enjoyed it.
I took the JM Portilla's other course titled "Complete Python Bootcamp" and was impressed.
Read more
become a data scientist
It cites average salaries over $120K and quotes “Enroll in the course and become a data scientist today!” This is unfortunately not true, and the course should not be marketed in this manner.
I find myself looking up YouTube videos to gain understanding of the concepts presented in the book, when I would have expected these concepts to be explained by Jose throughout the course since it advertises on helping you become a Data Scientist.
Yes, We are getting the overall path to become a data scientist.
I am really happy to continue with Jose on my path to become a data scientist!
very nice and very useful stuff for to become a data scientist..
If you want to become a data scientist you MUST take this course.
Perfect lecture for a python& data analysis beginner to take a step forward to become a data scientist !
Read more
zero to hero
The first lesson (From Zero to Hero) from the same author was good.
I did not know anything about data science prior to this course, but I have taken a prior Udemy course "Python zero to hero" with author Tim to get introduced deep into Python language.
After watching some of the introductory videos, I wasn't sure if I actually had a good enough Python foundation (I had only taken one beginner course on EdX), so I took Jose's "Zero to Hero" Python course.
I have completed Python Bootcamp : Zero to Hero course before this one and it was really well explained and easy to understand with lots of real time examples and projects.
Able to get through a lot of material at a steady pace I have previously done his python - zero to hero course.
If not, you may have a harder time (Jose's Zero to Hero Python bootcamp is amazing, btw).
I have already done the From Zero to Hero in Python Course by Jose Portilla.
Read more
boot camp
It definitely is a boot camp.
Great boot camp course.
This course is a great boot camp for python machine learning.
I watched his django series through until the django docs sufficed and I am now more than 50% through with his data science course boot camp.
perhaps not as thorough as on Jose's python boot camp course, but then again there is a fair amount of material here, and there must be some assumed knowledge.
Also, I am using the course as a reference for my data science boot camp.
It's a good basic course for anyone who wants to learn anything that is related to data analysis The instructor is very good; I've taken one of his courses (the Python boot camp) before.
Perfect next step after doing the Python Boot Camp course.
hi i am anantha, i find you are a professional in this i Like this Lectures and i have the python boot camp from you this cores is relay engaging and im havig fun lerning you cold improve this corse by adding more lectures thanks!
It is early so hard to say, but having quite a bit of programming background (less with python) it seems a better fit than the python boot camp I started with (which moved way to slow).
Read more
andrew ng
I knew Java and had completed Andrew Ng's Coursera foundation course and hence was looking for a way to learn Python and the implementation of things taught there.
I am doing this course after ML course from Andrew Ng at Coursera, it equips me with Python knowledge, I am pretty advanced in math so I am not spending time one theory very much.
I would recommend free Andrew Ng lectures on youtube for that.
This is unlike other courses where focus is more on theory (e.g., Andrew Ng's Machine Learning course or Geoffrey Hinton's NN course) - that has its own returns.
For the machine learning section, one need to go through the provided materials (or simply have the Machine Learning by Andrew Ng passed first as I did), otherwise may feel lost or confused because the topics are only touched upon.
I had taken the MIT intro to comp sci with python course and Andrew Ng's machine learning course, so I wanted the best way to put the theory into action- and this is a great way to go.
I'd say this is a perfect companion to Andrew Ng's course, it gives you the application rather than the heavy theory from Andrew's lecture.
Only suggestion I would recommend is to maybe provide more theory on the maths side (I am mainly interested in the Deep Learning topics) such as derivation of backpropagation from first principles for example the way Andrew Ng does in a broken down/visual way.
I finished Andrew Ng class in Coursera and this one is a very good complementary course to practice ML in Python Concise and very practical contents good for actual application!
Explains very well, easy to understand good, until now I like the pace Needed preparation for Andrew Ng's advanced courses in Machine learning, Deep learning, and so on.
Read more
wide range of topics
It covers a wide range of topics, all of which are vital for becoming a Data Scientist.
Very thorough and enjoyable course, covering a wide range of topics from Python basics up to TensorFlow DNNs.
Covers a wide range of topics and give brief overview over each machine learning techniques, great for getting started in the field.
This man is awesome , but this linear regression needs some more explaination Very good at covering a wide range of topics.
Read more
linear regression
It would have been nice if simple linear regression is explained with only 1 variable , and then move on to train test split method.
If there is more lecture about the assumptions of linear regression and how to check them, it would be even more great.
The students should have taken or knew the basics of statistics such as independent variables, dependent variables, linear regression etc.
The section on Linear Regression, for example, didn't even MENTION P values, t statistics, or any of the statistical tests necessary to properly implement a Linear Regression.
I just missed two things in the regression analysis sessions: 1 - The functional form a linear regression model was never shown in the linear regression session.
would look forward to the practice modules to be integrated.Concept of gradient descent could have been introduced at the level of linear regression/logistic regression, batch size etc I'm finding learning about data analysis and visualization very fun.
Besides, what amazes me is the introduction to machine learning with great lectures on each topic and also create a problem-solved project for linear regression, classification, and so on Great course, covered a range of topics with excellent clarity !
I thought it would walk me through linear regression coding, not just using a library.
Read more
line by line
He is great at breaking down what Python is doing line by line.
Going line by line with programming, gives us more clear picture.
Jose does a great job explaining the codes line by line with a steady pace...learnt a lot of cool stuff...i would recommend it anyone who is new to machine learning.
Thanks Jose good explanation line by line of code.
Definitely recommended for anyone who wants a line by line explanation along with great capstone projects.
Read more
las explicaciones
Buen contenido, las explicaciones son claras, todos los ejemplos son con buenos datos The course was excellent and the support was very helpful, unfortunately some of the lectures were outdated and I was unable to complete the big data/ spark section due to the online Jupyter notebook not loading and I could not get the help necessary for me to complete this section properly.
Empieza bien, parece bastante conciso en las explicaciones.
Le doy las 5 estrellas por la claridad en las explicaciones.
COOOOOOOOOOOOOOOOOOOOOOOOOOL Excelentes clases muy bien explicadas, con ejercicios solucionados con las explicaciones correspondientes.
:) las explicaciones son bastante claras aunque preferiria que el no se cubrieran tantas nociones basicas de python y que se entrase mas en materia.
De momento se entienden bien las explicaciones.
todo es muy claro y fácil de seguir Yes it was a good match for me as i am following in perfectly clear presentation Clear, informative, well judged and appropriately marketed youre very detailed, but little confusing wheter we first need to install anaconda, or notebook jupyter from www.jupiyter.org, Tons of good information for your learning pleasure All clear and easy to follow Couldn't expect more Jose is a very good instructor Hasta el momento las explicaciones son claras so far so easy to understand and follow along good voice its really good and well explained.
Read more
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Data Scientist - Big Data $68k
Data Review Scientist $81k
Data Scientist 1 3 $86k
Data Scientist - Data Curation $92k
Data Scientist 2 3 $99k
Energy Data Scientist $99k
Data Scientist 3 4 $99k
Data Scientist - P&C $102k
Data Scientist / Data Visualization $107k
Data Scientist 1 2 $109k
Research Scientist / Data Scientist $117k
Data Scientist, IT $156k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
Rating | 4.5★ based on 7,216 ratings |
---|---|
Length | 25 total hours |
Starts | On Demand (Start anytime) |
Cost | $12 |
From | Udemy |
Instructors | Jose Portilla, Pierian Data International by Jose Portilla |
Download Videos | Only via the Udemy mobile app |
Language | English |
Subjects | Data Science Business |
Tags | Data Science Business Development Data & Analytics |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course