The ‘Python for Data Science and Machine Learning Bootcamp Course’ is categorized as an intermediate-level course designed for those who have prior programming knowledge. The course is rated 4.6 out of 5 stars The course helps in learning the use of Python for analyzing data and creating beautiful visualizations as well as helps in using powerful machine learning algorithms.

Originally, this course is priced between INR 2,000 to INR 4,000. Students can Enroll Now and get an exclusive discount of up to 90% off the regular price by clicking on the link.

Course Highlights

Key HighlightsDetails
PriceStudents can Join Now and get a discount of up to 90% off the regular price (INR 3,399).
Duration25 hours
Student Enrollment6.27 lakhs
InstructorJose Portilla
Course Level (Resources Required)Intermediate (Programming Experience & Admin permission to download files)
Coding ExercisesYes
Total Student Reviews1.28 lakhs
  • This comprehensive course is equivalent to any other Data Science Bootcamps but is cost-effective
  • Learn to program with Python, using pandas to handle Excel, and web scraping with Python
  • This course can be pursued by anyone with some basic Data Science knowledge
  • Some sections are outdated
  • Completely focused on Python syntaxes with no sections on mathematics or statistics
  • Incorrect approach to solving problems

Learning Outcomes

  • Using Python for Data Science and Machine Learning
  • Implementing Machine Learning Algorithms
  • Using Spark for analyzing Big Data
  • Using NumPy for Numerical data
  • Using Seaborn for Statistical plots
  • Logistic and Linear Regression

Course Content

S. No.Module (Duration)Topics
1Python for Data Analysis – NumPy (1 Hour 04 minutes)Numpy Arrays, Numpy Operations, Numpy Array Indexing,
2Python for Data Analysis – Pandas (1 Hour 43 Minutes)Data Frames Part – 1,2,3, Missing Data, Groupby, Operations, Data Input, and Output
3Python for Data Visualization – Matplotlib (1 Hour)Matplotlib 1, 2, 3
4Python for Data Visualization – Seaborn (1 Hour 22 Minutes)Categorical Plots, Style and Color, Grids and Matrix Plots
5Support Vector Machines (35 Minutes) SVM Theory, Support Vector Machines with Python
6Natural Language Processing (1 Hour 19 Minutes)NLP With Python Part 1,2,3
7Big Data and Spark with Python (1 Hour 42 Minutes)Big Data Overview, Spark Overview, Local Spark Set up, AWS Account Set up
8Neural Nets and Deep Learning (5 Hour 2 Minutes)Perceptron Model, Activation Functions, Multi-class Classification Considerations, Cost Functions, and Gradient Descent

Resources Required

  • Prior Programming experience
  • Admin permissions to download files

Comparison Table

ParametersPython for Data Science and Machine Learning BootcampThe Data Science Courses 2023: Complete Data Science Bootcamp2023 Python for Machine Learning and Data Science Masterclass
OffersStudents can join the course now and get an exclusive discount of up to 90% off the regular price by clicking on the link.
Registration LinkApply Now!Apply Now!Apply Now!
Duration25 Hours29.5 Hours44 Hours
Rating4.6/54.6 / 54.7 / 5
Student Enrollments6.27 lakhs4.85 lakh59k
InstructorsJose Portilla365 Careers, 365 Careers TeamJose Portilla
Topics CoveredNeutral Nets and Deep Learning, Natural Language Processing, Support Vector MachinesProbability, Statistics, Python, Advanced Statistical Methods, Deep Learning, MathematicsNumPy, Pandas, Matplotlib, Linear Regression, Logistic Regression
Coding ExercisesYesNoYes
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Student Reviews

Check out the student reviews for the Python for Data Science and Machine Learning Bootcamp course,

  • Natalie P. (5.0/5): “Awesome course. Jose Portilla is a great instructor, his explanations are crystal clear and easy to follow. The best part of the course are the exercises, you have coding exercises for each ML algorithm, for each visualization library etc. Practice is the most important part in my opinion and not all courses here offer many (or any) exercises. If you get stuck, the solutions notebook guide you through each step. Many thanks Jose!’’
  • Saurabh K (5.0/5): “A very easy and clear to understand the concept dictated by the instructor. Learned a lot of new things looking forward to join some new course on machine learning. A big thanks to Mr. Jose Portilla.”
  • Mike M. (5.0/5): “Jose P. is a great instructor. He is well organize. He builds his lectures step by step from basic fundamentals to complex topics. He points out important steps to avoid faults later on. He speaks clearly. I think it is helpful to review some statistic course to explain the topics. although he mentioned a book you can follow.”
  • David M. (5.0/5): “This course was a really good. I came for the Python thinking it was a deep dive into python programming. The Visualizations was a bonus but eventually got over my head. That said the instructor,Jose, was really good and very thorough. Top Notch!! Highly Recommend!”
  • Soheel H. (5.0/5): “This is an excellent course! Jose is a very good instructor, and the course is kept up to date as software changes unlike some others on Udemy. The course is very practically oriented, and focuses on actually using Python and Jupyter to do analysis rather than spending too much time on machine learning theory. You do get a high level overview of the mathematics of each machine learning technique, which I think will be sufficient for most people. There are lots of projects within the course, which really help you learn and understand the content. For those of you interested in the details of the mathematics, I recommend following this course up with Andrew Ng’s excellent free course on Coursera, which complements this course very well.
  • Shalini D. (4.0/5): “the course gave me entire overview of data science , before this course i was too scared about machine learning topic, but sir has explained very well , now i’m too confident to explore more into machine learning topic. I really want to thank sir jose for this course and syllabus”
  • Atikant K. (4.0/5): “Helps someone who’s just finished with basics of Python to get into data analysis and machine learning. A good starting point, once you have a grasp of Python.”
  • Sukanya M (4.0/5): More expectation about the DL algorithms, so that how classification actually takes place would be clear for big data system. Multi Classification cases are not touched almost.
  • Ufuk Kadir E. (3.0/5): “The course is basically good. But there are a few sections that are quite outdated, especially the last section with AWS. While we, the students, obviously don’t ask Jose to refilm everything every time a new update occurs on platforms, there should be explanations with up-to-date information and appropriate answers to questions the students have asked. Often times the answers in the Q&A are short (and not satisfactorily explained), and there are sometimes no answers at all. For me, for example, the lecture on AWS and Spark was completely undoable because I could not set it up even though I did all the steps some of the students have suggested (but no suggestion was given by either the TAs or Jose). If you still sell the course, then you have the obligation to update what you periodically check and find material that needs updating. Otherwise, it is just a bad reputation and falling behind of other platforms like MITx.”
  • Matt H. (3.0/5): “Overall, the course is useful, easy to follow and covers a good amount of ground. The issue I have with it though is that it is poorly maintained, and some of the content is several years out of date (e.g. solutions including functions/methods that were deprecated from Python a long time ago). While a slight lag here is forgivable, and any course will always be a little bit behind the latest versions of Python and specific libraries, it doesn’t sit well with me that the instructor keeps the same outdated content for years while continuing to make money from selling the course. It’s not a bad course at all – I just think it would be a lot better if the content were kept up-to-date.”

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Python for Data Science and Machine Learning Bootcamp: FAQs

Ques. Is Python for data science and machine learning Bootcamp good?

Ans. Python for data science and machine learning Bootcamp is an amazing course with well-detailed modules and projects,

Ques. Which Python course is best for data science?

Ans. Some of the best python courses are,

  • Complete Data Science Training with Python for Data Analysis [Udemy]
  • Python Basic for Data Science [edX]
  • Python for Data Science Course [Datacamp]
  • Data Science with Python Certification Course [Simplilearn]
  • Master Python for Data Science [Linkedin Learning]

Ques. How good is the Udemy data science course?

Ans. Udemy Data Science courses are one of the best, as it has over 10,000 courses out of which more than 500 are free courses. One can choose to specialize in Python, Tableau, etc.

Ques. Who is Jose Portilla?

Ans. Jose Portilla is an instructor and trainer for Data Science Programming.

Ques. Is Jose Portilla’s course worth it?

Ans. Yes, his courses are a great source of knowledge for students who wants to learn Python.

Ques. Which data science course is best on Udemy?

Ans. The best data science course on Udemy are,

  1. The Data Science Course: Complete Data Science Bootcamp
  2. Data Science A-Z: Real-Life Exercises
  3. Python for Data Science & Machine Learning
  4. Complete Data Science & Machine Learning Bootcamp
  5. Statistics for Data Science and Business Analysis

Ques. Which certification is best for data science?

Ans. The best Data Science Certificates are as follows,

  • SAS Advanced Analytics Professional Certification
  • SAS Certified Data Curation Professional
  • DASCA: Senior Data Scientist
  • Microsoft Certified: Azure Data Scientist Associate
  • IBM Data Science Professional Certificate
  • HarvardX’s Data Science Professional Certificate

Ques. What is the best Python for machine learning?

Ans. NumPy is the best and popular python library for large multi-dimensional array and matrix processing.

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