Enrolled: 8 students
Duration: 216 hours
Lectures: 11
Level: Beginner

Working hours

Monday 10:00 am - 7:00 pm
Tuesday 10:00 am - 7:00 pm
Wednesday 10:00 am - 7:00 pm
Thursday 10:00 am - 7:00 pm
Friday 10:00 am - 7:00 pm
Saturday 10:00 am - 7:00 pm
Sunday 10:00 am - 7:00 pm

Data Science is the science of mining and analyzing available data at a granular level using various known algorithms and techniques. It also helps to uncover hidden findings to derive business productive insights. The knowledge and valuable insights extracted by studying the complex behavior and patterns of the available data, helps organizations to predict future trends & risks. It also helps in making better business decisions and strategies to reduce risks.

Data Science includes Artificial Intelligence, Machine Learning and Deep Learning and also tools such as Excel file, Tableau, Power BI etc. Deep Learning helps us to interpret and achieve insights using multi neural network architecture. Deep learning is a subset of Machine Learning that helps in building artificial intelligence.

Why should you enroll for this course?

  • Candidates aspiring to make a career in Data Science need to understand the concepts and principles of Deep L
  • Deep Learning finds its application in some of the most demanded careers in AI.
  • Deep Learning plays a crucial role in training vision based Artificial Intelligence programs and thus is widely applied in image recognition tools.
  • Deep Learning provides a mechanism for predicting outcomes when we have huge data at our disposal to analyze and learn from.

1
Introduction to Deep Learning
2
Introduction to Neural Networks
3
Optimization Algorithm
4
How to build a NN from scratch
5
Deep learning Tensorflow 2.0 introduction
6
Introduction to Deep NN
7
Deep learning Over fitting
8
Deep learning Initialization
9
Gradient descent & learning rate schedules
10
Preprocessing
11
Case Study Mnist Data set

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