Diploma in Python with Data Science and Machine Learning course will teach students how to write in Python and help to advance their career. Students who enrol in the diploma programme in Python programming progress from the fundamentals of creating and running scripts to more complex capabilities like file operations, regular expressions, and working with binary data.
One of the most effective, adaptable, and potent open source languages is Python, which has applications in signal processing, finance, oil and gas, physics, and scientific computing. The market share of this programming language has recently started to grow. Python programming is cross-platform, making it possible to use it more effectively for a variety of tasks on any operating system. Python is an exception to all of this because it is easy for anyone with programming experience to use. The courses are usually available at INR 3,499 on Udemy but you can click now to get 87% off and get Diploma in Python with Data Science and Machine Learning for INR 449.
Who all can opt for this course?
- Students who are interested to learn python programming can opt for this course
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 29.5 Hours |
| Rating | 4.0/5 |
| Student Enrollment | 46,482 students |
| Instructor | Global Education Foundation https://www.linkedin.com/in/globaleducationfoundation |
| Topics Covered | Python Programming, Data Analysis, Machine Learning, Data Science, and Java |
| Course Level | Intermediate |
| Total Student Reviews | 457 |
Learning Outcomes
- Python with data science and machine learning
- Dictionary and lists for Python data types
- Learn in-depth Java programming
- Master Java and data science
- Learn about Python and artificial intelligence
- Understand Multithreading
- Learn from ongoing projects
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Coding in Python (42 minutes) | 2.1 Variables in Python |
| 2.2 Data Types | ||
| 2.3 Lists in Python | ||
| 2.4 Demo of List function | ||
| 2.5 Tuples | ||
| 2.6 Python Dictionary | ||
| 2. | Core of Python in depth (16 minutes) | 3.1 Python Operators |
| 3.2 If Else statement | ||
| 3.3 Indentation | ||
| 3.4 Assignment 1 | ||
| 3. | Multithreading in Python (07 minutes) | 4.1 Iterative Statements |
| 4.2 While Statement | ||
| 4.3 For Statement | ||
| 4.4 Touple | ||
| 4.5 Assignment 2 | ||
| 4. | Demonstration (25 minutes) | 5.1 Demo 1 For loop |
| 5.2 Demo 2 While loop | ||
| 5.3 Demo 3 Range function | ||
| Test 1 | ||
| Test 2 | ||
| 5. | 6 Python Bootcamp (01 hour 02 minutes) | 6.1 Python Bootcamp Introduction |
| 6.2 Data Science & ML introduction | ||
| 6.3 Python Crash Course Introductory | ||
| 6.4 Python Crash course lecture 1 | ||
| 6.5 Dictionaries in Python | ||
| 6.6 Jupiter Python Exercises | ||
| 6.7 Operators in Python | ||
| 6.8 Iterative Statements | ||
| 6.9 Python Functions | ||
| 6. | Data Analysis Numpy series (58 minutes) | 7.1 Data Analysis Numpy Part 1 |
| 7.2 Data Analysis Numpy Part 2 | ||
| 7.3 Data Analysis Numpy Part 3 | ||
| 7.4 Data Analysis Numpy Part 4 | ||
| 7. | Data Analysis Pandas (55 minutes) | 8.1 Data analysis Pandas part 1 |
| 8.2 Data analysis Pandas part 2 | ||
| 8.3 Data analysis pandas Part 3 | ||
| 8.4 Data analysis pandas Part 4 | ||
| 8.5 Data Analysis Pandas Part 5 | ||
| 8.6 Data Analysis Pandas Part 6 | ||
| 8.7 Data Analysis Pandas Part 7 | ||
| 8. | Data Visualization Matplotlib (23 minutes) | 9.1 Data Visualization Matplotlib Part 1 |
| 9.2 Data Visualization Matplotlib Part 2 | ||
| 9. | Data Visualization seaborn (16 minutes) | 10.1 Data Visualization seaborn Part 1 |
| 10.2 Data Visualization seaborn Part 2 | ||
| 10. | Machine Learning (18 minutes) | 11.1 Machine Learning part 1 |
| 11.2 Machine Learning part 2 | ||
| 11. | (BONUS SERIES) Java Programming (13 hours 54 minutes) | 1. Java introduction |
| 2. Variables in Java | ||
| 3. Identifiers in Java | ||
| 4. Reserved Keywords in Java | ||
| 5. Literals in Java | ||
| 6. Arrays in Java | ||
| 7. Strings in Java part 1 | ||
| 8. Strings in Java part 2 | ||
| 09. Operators in Java | ||
| 10. Type Casting in Java | ||
| 11. Control statement If else in Java | ||
| 12. Switch Statement in Java | ||
| 12. | Advanced Machine Learning (01 hour 28 minutes) | 01. MachineLearning introduction |
| 02. Types of Machine Learning | ||
| 03. Unsupervised Learning | ||
| 04. Supervised Learning | ||
| 05. Case study | ||
| 06. Bayes Theorem | ||
| 07. Support Vector Machine Algorithm | ||
| 08. KNN Algorithm | ||
| 09. Decision Tree | ||
| 10. Hierrarchical Clustering | ||
| 11. K Means Algorithm | ||
| 13. | Speech Recognition by Python ( Mini Project ) (38 minutes) | Speech recognition course |
| Computer vision lecture 1 | ||
| Computer vision lecture 2 | ||
| Computer vision lecture 3 | ||
| Computer vision lecture 4 | ||
| Computer vision lecture 5 | ||
| 14. | Project Based Learning and Mini Project (01 hour 39 minutes) | PBL1 |
| PBL2 | ||
| PBL3 | ||
| PBL4 | ||
| PBL5 | ||
| PBL6 | ||
| PBL7 | ||
| 15. | Web Development Bootcamp (01 hour 49 minutes) | 1. Web development 1 |
| 2. Web development 2 | ||
| 3. Web development 3 | ||
| 4. Web development 4 | ||
| 5. Web development 5 | ||
| 6. Web development 6 | ||
| 7. Web development 7 | ||
| 8. Web development 8 | ||
| 9. Web development 9 | ||
| 10. Web development 10 | ||
| 11. Web development 11 | ||
| 16. | CSS (02 hours 05 minutes) | Web Development CSS 1 |
| Web Development CSS 2 | ||
| Web Development CSS 3 | ||
| Web Development CSS 4 | ||
| Web Development CSS 5 | ||
| Web Development CSS 6 | ||
| Web Development CSS 7 | ||
| Web Development CSS 8 | ||
| Web Development CSS 9 | ||
| Web Development CSS 10 | ||
| Web Development CSS 11 | ||
| 17. | JavaScript (01 hour 56 minutes) | JavaScript 1 |
| JavaScript2 | ||
| JavaScript3 | ||
| JavaScript4 | ||
| JavaScript5 | ||
| JavaScript6 | ||
| JavaScript7 | ||
| JavaScript8 | ||
| JavaScript9 | ||
| 18. | Revision Lectures (33 minutes) | Revision1 |
| Revision2 |
Resources Required
- A desktop computer that can run Python on Windows, Mac, or Linux
- Prior coding or scripting experience
Featured Review
Ismail Mohammed G. (5/5) : Best decision I ever made, I hope to learn and understand more. great job!
Pros
- Ephesian Solomon (5/5) : It’s amazing, the teacher understanding has made it easier for me now.
- Jorico B. (5/5) : Thank you so much for giving a chance to learn more about programming specially in python.
- Tiwari Dolly R. (5/5) : Good to learn
Cons
- Harry Syan (1/5) : Matter is not good, and tutor is not audible, there are lot of interference in the background.
- Vineet Verma (1/5) : This course was worse than the worst Youtube videos…literally a complete waste of time not matter what your skill level is…you could get better knowledge in youtube
- Rafael Kawamura (1/5) : My impression so far is: bad audio quality, very 1st lesson seems to have a cut in the end and it felt too rendundant.
About the Author
The instructor of this course is Global Education Foundation who is a Simplified Education should reach to all corners of World. With 4.1 Instructor Rating and 1,242 Reviews on Udemy, he/she offers 25 Courses and has taught 83,883 Students so far.
- The main goal of the instructor is to spread simplified education throughout the entire planet
- Global Education Foundation is a global organisation that has offices in 127 nations
- The mission of the instructor is to research and advise on the use of information technology, artificial intelligence, machine learning, VFX, graphic design, virtual reality, automation, motion pictures, cloud computing, ANN (RL), and software programming in the industry
- Together with the subsidiary Civil Info-Tech Consultants, Instructor is working in the education sector as part of the social responsibility and for impoverished students who cannot afford higher education
- The students of the course are studying sophisticated methods for tackling problems
- Team Global Education Foundation has embarked on a new path while utilising its expertise in education and consultation
Comparison Table
| Parameters | Diploma in Python with Data Science and Machine Learning | Python for Machine Learning with Numpy, Pandas & Matplotlib | Advanced Foundations of Python Programming | 2023 Training |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 29.5 hours | 7 hours | 4 hours |
| Rating | 4.1 /5 | 4.3 /5 | 4.1 /5 |
| Student Enrollments | 46,482 | 104,635 | 87,346 |
| Instructors | Global Education Foundation | Code Warriors | SDE Arts | Octavo |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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