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Virtual Reality with AI and Data Science

Virtual Reality with Artificial Intelligence 
                        training in Kochi, Kerala

Virtual Reality AI and Data Science (12 Months)

Developing Virtual reality use cases using Generative Adversarial Network (GAN). Occulus Rift/Go Simulations will be developed with interactive animation using Unity 3D. Course Includes use cases such as Computer Vision, Chatbot, Speech Recognition, Hand written text recognition, Spam Detection, Optical character recognition etc.

What is Virtual Reality with AI and Data Science

Data Science is a core software development skill where Deep Learning is the heart. Data Analytics is the pre-processing activities of Data Science. The preprocessed data is generally used for Machine Learning Modelling. The time taken to run Data Science tasks are critical, When that concerned for huge amount of data to be processed to generate some significant information for decision making. Thus generally Data Science works with Big Data Analytics as well. These skills are generally needed together to make any important usecase completion. Deep Learning is a kind of automated Machine Learning. That means the preprocessing activities are not planned as a predecessor step. However the sampling, featurisation and vectorization are inherent process like automated machine learning in Deep Learning. Virtual reality is a similation of real world in 3D with the help of AI. Generative Adversarialy Network is the technology used to tranform faces between Genders, or a younger face to and older one. Virually the faces, Music and other simulations are created and animated using unity 3D and view through occulus Rift/Go devices.

Technologies

Advanced Python Programming (2 Months)
Complete Python programming with Advanced features like Django programming, Visualization using Seaborn and matplotlib graphs, Data re-shaping with Numpy and Pandas.
Machine Learning SciKit Learn (2 Months)
Machine Learning Libarary that supports, Regression, Logistic Regression, Classification, Clusterig, Decision Tree, Random Forest, Statistical algorithms and probability distributions.
Deep Learning TensorFlow and Keras (2 Month)
The number one choice of programmers to implement the Deep Learning Use cases. Direct acyclic Graphs are used to store the relationships. Python based Deep Learning extension over Tensorflow. Keras is widely used for Neural network topology planning, training and execution. CNN, RNN, LSTM and other advanced artificial nueral network use cases can be implemented using Keras Easily.
Virtual Reality with Gen AI (4 Months)
GAN, Advanced NLP, Generative AI, Large Language Models (LLM), Text Generation, Image Generation, Video Generation, Transformers, Attention and Word Embedding, Positional Encoding, Foundation Model and fine tuning, Prompt and Context configuration, Introduction to AWS SageMaker and Bedrock
Cloud Computing (2 Months)
AWS hosting, Regiions and Zones, Availablity Group, Load Balancing, Docker, Kubernetes, ESB, S3 Bucket, AMI Security configuration, RDS, MongoDB etc.

Syllabus

Expertzlab Data Science course in Kochi contains all the industry required contents and all of them will be implemented in the class with appropriate project use cases. Students will have immense experience in writing code and thus this Data Science training program is a easy gateway to an IT Job as Software Developer.

    Python and Web Design Syllabus (2 Months)
    Machine Learning Syllabus (2 Months)
    Deep Learning Syllabus (2 Months)
  • Generative AI, LLM, Distributed Learning and Optimisation, GAN, AutoEncoders, Transformers, Translearning.
  • Projects:
  • Speech to Text and Text to Speech conversions: MFCC, Mapping speech to Matrix, Creatingl Spectrograms
  • Speech Recognition Classifier, Resample audio, Preprocessing audio wave, convert to deep learning model
  • Building Keras models, Diagnostic Plot, Predictions, Text to Speech, loading waves, CNN models for wave predictions
  • Chatbot from Scratch: Developing chatbots, Retrieval based chatbots, Generative based chatbots, LSTM for chatbot
  • Context, Design of chatbots, Steps for building chatbots, Preprocessing data and loading data, Lemmatize, training and testing
  • Predict Response, Random Intents, Executing Chatbots, Chatbots using CNN, Genism, use of Genism, Wordvec, Intent classifier

How Expertzlab is different from other institutes How Expertzlab is different from others

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