Learn Data Science/ML with Practical Hands-On Projects and Deployment. (Flask,Heroku,AWS,Google Cloud,Microsoft Azure)
What you'll learn
- Master Machine Learning With Python
- Learn Through More Than 20+ Projects and Assignments
- Learn How to Deploy Machine Learning Models
- Practical Hands-On Data Science Projects Mastery
- Build And Deploy On Flask, Heroku, Streamlit, AWS,Google Cloud, Microsoft Azure
- Create Robust Machine Learning Models
- Learn Different Machine Learning Algorithms such as Linear And Logistic regression, Naive Bayes,KNN,SVM,K-means, etc.
- Deal With Data Imbalance (Upsampling/Downsampling/SMOTE)
- Beginner To Advance
- Gain Confidence In Performing Exploratory Data Analysis (EDA)
- Choose The Right Machine Learning Model For Your Problem Statement
- Access To Exclusive Community To Learn With Others And Answer Your Queries
- Learn The Necessary Statistics
- Master Data Analysis
- This course is a beginner to advance level course with all the tutorials on the lessons covered in the projects included
- If you are a complete beginner, you have all the lessons from introduction to python to building projects and deployment.
- If you already have have the basics, we have more than 20 projects and deployment for you to practice.
Interested in the field of Data Science and Machine Learning?
Interested in Building Data Science and Machine Learning Projects and Deploy on Platforms such as AWS, Google Cloud, Microsoft Azure, Heroku, Flask, Streamlit?
Interested in learning it the practical way?
Then this course is for you!!
This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects throughout the course.
This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding.
We will walk you through step-by-step on each topic explaining each line of code for your understanding.
There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.
We have structured the course in this way:
- Python For Data Science
- Statistics For Data Science
- Machine Learning
- Hands-on projects on each topic
- Projects Deployment Tutorial
- Streamlit project tutorial
- Flask deployment project tutorial
- Heroku deployment project tutorial
- Google cloud deployment project tutorial
- AWS deployment project tutorial
- Microsoft Azure deployment project tutorial
Who this course is for:
- Anyone interested in Data Science and Machine Learning.
- Anyone who wants to Build And Deploy machine learning models on Flask, Heroku, AWS,Google Cloud, Microsoft Azure
- Any student interested in a career in Data Science and Machine Learning
- Any beginner level interested to kick-start their career in Data Science and Machine Learning
- Any intermediate level learner who know the basics of python, statistics, machine Learning and want to learn more about it
- Anyone not that comfortable with coding but interested in Data Science and Machine Learning and want to easily understand the concepts
- Any data analysts who want to transition to Data Science and Machine Learning
- Any Business Analysts who want to transition to Data Science and Machine Learning
- Anyone not satisfied with their job and looking for a career transition to become a Data Scientist.
- Anyone who wants to leverage the power of data in his case scenario.
- Any curious mind