Data Science and Machine Learning for Non Programmers | Data Science for Beginners | Edureka

** Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training **
This Edureka video on "Data Science and Machine Learning for Non-programmers" is specifically dedicated to non-IT professionals who are trying to make a career in Data Science and Machine Learning without the experience of working on programming languages. Here’s a list of topics that are covered in this Data Science for Beginners session:

Introduction to Data Science and Machine Learning
Data Science and Machine Learning Domains
Questions Every Non-Programmer Has
Data Science and Machine Learning Tools For Non-Programmers

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About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

The Master's Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.

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Prerequisites

There are no prerequisites for enrollment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

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Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information