Certification Course

MLOps - Machine Learning & Deep Learning with DevOps and AWS Sagemaker (Cloud)

Learn with Mr. Prateek Mishra

₹ 25000 /-

₹ 4000 /-



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Mr. Prateek Mishra
Founder & Chief of TechSim+
Review
    4.9
Categories
AI & ML Courses

Overview

  • Lectures 40 - 45
  • Duration 45 Days
  • MemberShip Yes
  • Projects Yes
  • Skill level Basic to Advanced
  • Language English
  • Assessments Yes
Course Description

Data Analytics, Machine Learning and Deep Learning on DevOps with AWS Sagemaker using Python helps you gain expertise in various machine learning algorithms such as regression, classification, clustering, decision trees, random forest, Naïve Bayes K-NN and More. We will cover deep learning algorithms like FNN, CNN, R-CNN, GANs, etc. We also work on Transfer Learning and make different projects. Apart from this, you will work on DevOps tools and install these on AWS Cloud. In This training you will not only work on technologies, but you will also make industry-related projects and deploy these projects on the cloud.

Learning Outcomes
  • Hands on Practical based Training.
  • Get Placement Opportunity in AI - ML Companies.
  • Live project based on any of the selected use cases, involving implementation of Data Science with Python.
  • TechSim+ certifies you in Data Analytic and Machine Learning with Python
  • Get Certified by IIT's and NIT's
  • Get one Year Membership with TechSim+.
  • Make different Types of Projects during Training

Curriculum

Download Curriculum

    Python with Data Analysis

    In this Part You will get a brief idea of what Python is and Why it’s Important. You will learn Python basic and Advance for ML. After completing Python we will focus on Data Analysis and Data Visualisation with the help of different libraries like: NumPy, Pandas, MatplotLib, Seaborn and Plotly.


  •     Introduction
  •     Python for Data Science and AI
  •     Introduction to Data Science
  •     Advanced Data Analysis – Pandas and bamboolib
  •     Data Visualisation with MatplotLib, Plotly and seaborn
  •     Project
  • Machine Learning with Python

    After Completing the Data Analytic you will learn Machine Learning. In this part you will understand how ML works. How you can train your machine with your data. We will work on different machine learning algorithms and make different projects.


  •     Closer Look - ML Working
  •     Math for Machine Learning and Deep Learning
  •     Supervised Machine Learning Algorithms – I
  •     Supervised Machine Learning Algorithms – II
  •     Un-Supervised Machine Learning Algorithms
  •     Project
  • Deep Learning and Image Processing with TensorFlow and Keras

    This is the Advanced part of Machine Learning called Deep Learning. In this part we will work on neural Networks. We will use different libraries for creating smart systems, like TensorFlow and Keras. You will work on different DL Algorithms like FNN, CNN, R-CNN, RNN and others.


  •     Neural Network Basics and Deep Learning
  •     Advanced Deep Learning Algorithms
  •     Advanced Transfer Learning with Image Processing
  •     Project
  • DevOps on AWS

    In this module you will be introduced to DevOps environment. you will learn about the different actions performed through git and will be introduced to Jenkins, maven, Dockers and others. You will learn about AWS Services and Install DevOps tool on AWS cloud. You will deploy machine learning on DevOps cloud.


  •     Introduction to DevOps.
  •     Infrastructure Setup on AWS – EC2
  •     Continuous Deployment: Containerization with Docker
  •     Project
  • AWS: Sagemaker, Machine Learning and Deep Learning

    This is again very important part of our Training. Here you will learn about AWS Sagemaker service. In Sagemaker you can built your machine learning and Deep Learning model very easily and deploy on AWS.


  •     Introduction and Setup
  •     Amazon Sagemaker Algorithms
  •     Project

Instructor

Mr. Prateek Mishra
Founder & Chief of TechSim+

Prateek is an entrepreneur and thought Leader in Artificial Intelligence deep-tech industries. He is a leading trainer with expertise in AI, Machine Learning, Data Analytics, Deep Learning, Python, Embedded and IOT, Flutter, Julia Programming, Blockchain, and Tableau. He trained 5000+ Students.

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