Python for Data Science and Machine Learning Beginners course walks through the programming prerequisites for a data scientist. This course is designed for absolute beginners in data science and machine learning. In this course, students will learn all aspects of Python necessary for data science, machine learning, and deep learning.
The courses are usually available at INR 3,499 on Udemy but you can click now to get 87% off and get Python for Data Science and Machine Learning Beginners Course for INR 449.
Who all can opt for this course?
- Python newbie who is interested in Data Science
- Programming Beginners
- Novice Data Scientists
- Machine Learning Beginners
Course Highlights
Key Highlights | Details |
---|---|
Registration Link | Apply Now! |
Price | INR 449 ( |
Duration | 07 hours |
Rating | 4.0/5 |
Student Enrollment | 16,042 students |
Instructor | Jay Bhatt https://www.linkedin.com/in/jaybhatt |
Topics Covered | Python Arithmetic Operations, Python Basics, Pandas, Data Science, etc. |
Course Level | Beginner |
Total Student Reviews | 1,069 |
Learning Outcomes
- Put machine learning algorithms into practice
- Learn how Python can be used for machine learning and data research
- Utilize multidimensional array operations and Numpy
- Analyze exploratory data using Pandas profiling
- Utilize Matplotlib and Plotly to create intricate visualizations
- Use Scikit-learn for machine learning tasks
- Decision Tree and Random Forest
- Learn Statistics for Machine Learning and Data Science
Course Content
S.No. | Module (Duration) | Topics |
---|---|---|
1. | Introduction to Python (04 minutes) | Course Promo |
Thank You | ||
How to get 100% from this course | ||
2. | Setting up environment and jupyter notebook (17 minutes) | Python Environment setup |
3. | Module -2 Python Arithmetic operations (15 minutes) | Terminology Alert |
Arithmetic Operators in Python | ||
Student Community | ||
4. | module 3- Python basics list string dictionary (36 minutes) | Module Intro |
Terminology Alert | ||
Python-Strings | ||
Terminology Alert | ||
Python-list | ||
Python-Dictionary | ||
5. | Numpy -Array Attributes (38 minutes) | Module Intro |
Terminology Alert | ||
Numpy-Basic array operations | ||
Matrix operations in numpy | ||
Terminology Alert | ||
Numpy-Random-Numbers | ||
Terminology Alert | ||
Numpy-advanced | ||
6. | Pandas (37 minutes) | Module Intro |
Pandas part1 | ||
pandas part 2 | ||
pandas part 3 | ||
pandas part4 | ||
7. | Matplotlib- Introduction (32 minutes) | Matplotlib-Introduction |
matplotlib1.1 | ||
Matplotlib 1.2 | ||
Matplotlib1.3 | ||
Pandas with matplotlib | ||
Matplotlib advanced Exercise | ||
8. | Introduction to Data Science (02 hours 01 minutes) | Introduction to Data Science |
Data Science with Python Part 1 | ||
Data Science with Python Part 2 | ||
Data Science with Python Part 3 | ||
Data Science with Python Part 4 | ||
Data Exploration Part 1 | ||
Data Exploration Part 2 | ||
Data Exploration Part 3 | ||
T-Test | ||
T-test in Python | ||
Z-Test | ||
Chi-Square Test | ||
Bivariate Exploration 1 | ||
Bivariate Exploration 2 | ||
Bivariate Exploration 2 | ||
Modelling basics | ||
what is linear regression | ||
Gradient Descent with linear regression | ||
9. | Create simple machine learning models with sklearn (16 minutes) | sklearn Intro |
sklearn part 1 | ||
Sklearn part 2 | ||
10. | Flight Delay Prediction with real world data (53 minutes) | Flight Delay Prediction Introduction |
Flight Delay Prediction Data Pre-processing | ||
Flight Delay Prediction Feature Generation | ||
Flight Delay Prediction with Random Forest | ||
Flight Delay Prediction final | ||
11. | Anaconda environment and conda cheat sheet (18 minutes) | Optional: Anaconda Virtual Environments |
12. | Bonus Lectures (01 hour 09 minutes) | Playing with Python codes |
Creating dashboards | ||
creating charts with Python | ||
Live video Transformation with Python | ||
Data Science Interview Questions |
Resources Required
Basic Mathematical knowledge
Featured Review
Ronaldo (5/5): best course I have ever taken it takes some time to build up the momentum.
Pros
- Auston (5/5): I will say this is the best course on udemy for Python and data science beginners
- Johnny (5/5): Well planned detail course for Python starters with very good practical exposure.
- Amitha V Renu (5/5): The way he taught was good and he will also guide us for interview.
- Amitha V Renu (5/5): Questions they may ask and what we need to answer it was good
Cons
- Girish Kumar T. (3.5/5): Please use more number of examples for frequently used models/modules will help us understand more easily.
- Sagar S. (3/5): It is good but a bit fast and unclear.
- Yash S. (1/5): Instructor not responding to questions in a timely manner. Still hasn’t responded to some of mine that I asked weeks ago.
- Ch Dhanyanjaya P. (1/5): Exepcted the detail explanation of the statistics terms and what is expected from the Model and some real-time business examples.
About the Author
The instructor of this course is Jay Bhatt who is a Data Scientist by profession and instructor by passion. With a 3.8 instructor rating and 3,446 reviews on Udemy, he offers 3 courses and has taught 28,536 students so far.
- He has completed his master’s degree in advanced mathematics and FEM and has five years of experience working for a reputable Data Science company.
- He adores producing instructional stuff and films.
- He hopes that students enjoy the Data Science and Machine Learning journey.
Comparison Table
Parameters | Python for Data Science and Machine Learning Beginners | Internet of Things with Python Programming | Python & R Programming |
---|---|---|---|
Offers | INR 455 ( | INR 455 ( | INR 455 ( |
Duration | 7.5 hours | 30.5 hours | 25 hours |
Rating | 4.0 /5 | 4.1 /5 | 4.2 /5 |
Student Enrollments | 16,042 | 26,641 | 45,959 |
Instructors | Jay Bhatt | Sai Acuity Institute of Learning Pvt Ltd Enabling Learning Through Insight! | Sai Acuity Institute of Learning Pvt Ltd Enabling Learning Through Insight! |
Register Here | Apply Now! | Apply Now! | Apply Now! |
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