4.97 (901 reviews)
☑ Implement Machine Learning Algorithms
☑ Use python for Data science and Machine Learning
☑ Use Numpy and multidimensional array operations
☑ Do exploratory Data analysis with pandas profiling
☑ Create complex visualization with matplotlib and plotly
☑ Use Scikit-learn for Machine Learning Task
☑ Linear Regression
☑ Random Forest and Decision Tree
☑ Statistics For Data Science and Machine Learning
Hi all Its Jay I am a data scientist by profession and Instructor by passion I have around 4 years of experience as data scientist, I started my career as analyst as gradually moved to data scientist hence I can understand what are programming prerequisites for data scientist. This course is created for absolute beginners of data science and machine learning. It covers all aspect of python languages required in data science machine learning and deep learning.
How to get 100% from this course
Setting up environment and jupyter notebook
Intro to module 1
Installing anaconda and setting up jupyter notebook
Anaconda environment and conda cheat sheet
Module -2 python Arithmetic operations
Arithmetic Operators in python
module 3- python basics list string dictionary
Numpy -Array Attributes
Numpy-Basic array operations
Matrix operations in numpy
pandas part 2
pandas part 3
Create simple machine learning models with sklearn
sklearn part 1
Sklearn part 2
Numpy and pandas explained very well however you can add more examples of real time modeling in the course overall very good.
course is pin pointed loved the approach and examples provided for every single concept.. looking for more
loved the professional behavior of instructor well designed course slow in start but keep up speed with time
It is all about the environment until now. The Data Science or the machine learning haven't been explained yet
Exepcted the detail explanation of the statistics terms and what is expected from the Model and some real-time business examples
• Teaching style to different audiences with ease and professionalism • Responds professionally to challenging audiences. Listens and provides a mature, respectful response. • Demonstrates patience and respectful guidance when interacting. • Stays current with the latest trends and innovations in training materials. • Uses technology in a learning environment with ease; demonstrates high computer proficiency and pictorial representation. • Evaluates the transfer of learning consistently and applies the findings by making changes where appropriate in materials. Really liked content and ease of telling and sharing knowledge. Recommends to all those want to start their career in data science and explore knowledge.
So for I liked the way instructor has used real life example to explain tough mathematical concept like z-test,t-test and all.
The way he teached was good and he will also guide us for interview. Questions they may ask and what we need to answer it was good
The instructor is energetic. Very good presentation I will say its was a masterpiece. I have never done coding before in my life as the course was so smooth that I never felt left out. looking ahead for other courses on deep learning..
Step by Step approach of the instructor is awesome. As a beginner I loved the instructor's approach thanks for creating such masterpiece...
The statistics and linear regression part was the most I loved. I can't imagine that the concept can be explained in such a simple way kudos for your work..
Amazing course, explains very complicated things in simple and bite-size terms. Loved the real time coding
I already took several courses about basic python on Udemy in order to get different perspectives. This one is clearly the best. I love the concept and the way the instructor explains with real time coding
your step by step approach is awesome as I am starting for zero I liked the way you explain however can you upload some of the lectures for mac os as most the examples are given for windows
Please use more number of examples for frequently used models/modules will help us understand more easily