Description
Academy of Computing & Artificial Intelligence proudly present you the course “Data Engineering with Python”. It all started when the expert team of Academy of Computing & Artificial Intelligence (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2021.
At the end of the Course you will be able to start your career in Data Mining & Machine Learning.
1) Introduction to Machine Learning – [A -Z] Comprehensive Training with Step by step guidance
2) Setting up the Environment for Machine Learning – Step by step guidance [R Programming & Python]
3) Supervised Learning – (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines (SVM), Random Forest)
4) Unsupervised Learning
5) Convolutional Neural Networks – CNN
6) Artificial Neural Networks
7) Real World Projects with Source
Course Learning Outcomes
To provide awareness of (Supervised & Unsupervised learning) coming under Machine Learning (Why we need Data Mining & Machine Learning, What is Data Mining, What is Machine Learning, Traditional Programming Vs Machine Learning, Steps to Solve a Data Mining & Machine Learning Problem, Classification , Clustering)
Describe intelligent problem-solving methods via appropriate usage of Machine Learning techniques.
To build appropriate neural models from using state-of-the-art python framework.
To setup the Environment for Machine Learning – Step by step guidance [R Programming & Python]
Convolutional Neural Networks – CNN
Resources from MIT and many famous Universities
Projects with Source
Who this course is for:
- Anyone who wish to start the career in Data Science & Machine Learning
Requirements
- Computer with Internet connection
- Python or any programming language
Last Updated 7/2021
Download Links
Direct Download
Machine Learning & Data Science Bootcamp with R & Python.zip (2.8 GB) | Mirror