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AI is a technology that has been gaining a lot of attention in the last few years. The need to develop artificial intelligence skills has been increasing at a fast pace. Experts predict that AI is the future and there is a ever growing demand among youngsters to join the bandwagon and develop their AI skills. 

JPA Training focuses on providing intensive AI training courses covering a wide range of topics such as Heuristic search, Markov decision processes, Machine learning etc. The training facilitates students to engage with various case scenarios and create diversified user perspectives. The course is structured for individuals looking to learn how they can impart AI in solving real time problems. 

After the completion of the course, our trained professionals are able to gain insights on roles played by Data Scientist, Techniques related to Data Transformation and Data Mining, Analyze Data using Machine Learning Algorithms, Explain Time Series and its Applications by working on Data Science Life Cycle and XML, CSV.  The Career field includes entry into many high paid jobs such as Gaming, Journalism, Robotics, Medical Fields.

Learning Objectives ::
 Becoming An Artificial Intelligence Engineer Puts You On The Path To An Exciting, Evolving Career That Is Predicted To Grow Sharply Into 2020 And Beyond. Artificial Intelligence Will Impact All Segments Of Daily Life By 2025, With Applications In A Wide Range Of Industries Such As Healthcare, Transportation, Insurance, Transport And Logistics And Even Customer Service.

AI Market ::
The New York Times Reports A Candidate Shortage For Certified AI Engineers, With Fewer Than 10,000 Qualified People In The World To Fill These Jobs, Which According To That, An Average Salary Of $172,000 Per Year In The U.S. For Engineers With The Required Skills.

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Skills You Will Learn ::
Design And Build Your Own Intelligent Agents And Apply Them To Create Practical Machine Learning Models, Logic Constraint Satisfaction Problems, Knowledge-Base Systems,Probabilistic Models.Understand And Master The Concepts And Principles Of Machine Learning, Including Its Mathematical And Heuristic Aspects.
Implement Deep Learning Algorithms In Keras Backend With Tensorflow. Understand Neural Networks, Empowering You To Analyze And Utilize Data In A Better Way.
Master Advanced Topics Such As Convolutional Neural Networks, Recurrent Neural Networks, Training Deep Networks And High-Level Interfaces
Learn About Major Applications Of Artificial Intelligence Across Various Use Cases In Various Fields Like Customer Service, Financial Services, Healthcare Etc
Ability To Apply Artificial Intelligence Techniques For Problem-Solving And Explain The Limitations Of Current Artificial Intelligence Techniques

Duration: 80 hours

Cost: $750/course
(excluding any certification cost)

Foundations Of AI

  • Python For Ai (Significant Functions, Packages And Routines)
  • Statistics & Probability (Descriptive & Inferential Stats, Probability & Conditional Prob)
  • Visualization Principles And Techniques
  • Linear Algebra
  • Calculus

Machine Learning: Supervised Learning

  • Regression (Linear, Multiple, Logistic)
  • Classification (K-Nn, Naïve Bayes, Svm) Techniques
  • Decision Trees

Machine Learning: Unsupervised Learning

  • Clustering (K-Means, Hierarchical, High-Dimensional)
  • Expectation Maximization

Machine Learning: Ensemble Method

  • Boosting And Bagging
  • Random Forests

Machine Learning: Associative Learning

  • Aprior
  • Eclat

Natural Language Processing

  • Statistical Nlp And Text Similarity
  • Syntax And Parsing Techniques
  • Text Summarization Techniques
  • Semantics And Generation
  • Topic Modeling (Lda, Tf-Idf)

Misc Topics

  • Hyper Parameter Tuning
  • Preprocessing Methodology
  • Elbow Method For Clustering
  • Ai Architecture For Generic Application Flow
  • Time Series Analysis

Computer Vision

  • Convolutional Neural Networks
  • Keras Library For Deep Learning In Python
  • Pre-Processing Image Data
  • Object & Face Recognition Using Techniques Above

Deep Learning

  • Neural Network Basics
  • Deep Neural Networks
  • Recurrent Neural Networks (Rnn) (Lstm, Gru, Dcn, Dmn, Bi-Daf)
  • Deep Learning Applied To Images Using Cnn
  • Tensor Flow For Neural Networks & Deep Learning
  • Poem Generator