Ria Academy offers its expertise in Data Science Program. Our tried and true system is based on over 10 years of cumulative experience shared between our trainers. We pride ourselves on setting up our clients for success in Data Science and AI operations and are sure that you will leave our sessions more prepared than you have ever been before to Machine Learning and Deep Learning courses.
Data Science Training In Bangalore
Ria Academy Offering The Best Data Science Training In Bangalore Marathahalli. and kick start your career as a successful Data Scientist within 4 months. Learn the advanced data science course concepts and get your skills upgraded from the pioneers in Data Science. Our training sessions are meticulously planned by our trainer and are designed in a manner geared toward the maximization of efficiency.
Your time is valuable, so our goal is to best prepare you while taking up the least amount of your time possible. Your Data Science Training In Marathahalli Bangalore will be conducted by 1 of our trainers, the total duration of this program is Data Science Course.
Do check our other courses from Ria Academy Software Courses in Bangalore Python Training, JAVA Training, C++ Training, SQL Training, and SAP Training. You can meet us at Ria Academy Data Science Course in Marathahalli. or you can just do a Live Chat with our experts if not WhatsApp from the website.
Sessions will be comprised of both activities and lectures that will touch upon the following subjects:
- Machine Learning
- Deep Learning
- Natural Language Processing
What Is Data Science? Who Is Data Scientist?
Data Science is all about mining hidden insights of data pertaining to trends, behavior, interpretation, and inferences to enable informed decisions to support the business. The professionals who perform these activities are said to be Data Scientists / Science professionals. Data Science is the most high-in-demand profession and as per Harvard and the most sort after a profession in the world.
- Introduction to Data Science with Python
- Python Basics: Basic Syntax, Data Structures
- Data objects, Math, Comparison Operators, Condition Statements, loops, lists, tuples, dicts, functions
- Numpy Package
- Pandas Package
- Python Advanced: Data Mugging with Pandas
- Python Advanced: Visualization with Matplotlib
- Exploratory Data Analysis: Data Cleaning, Data Wrangling
- Exploratory Data Analysis: Case Study
- Machine Learning Introduction
- What is ML? ML vs AI. ML Workflow, Statistical Modelling of ML. Application of ML
- Machine Learning Algorithms
- Popular ML algorithms, Clustering, Classification and Regression, Supervised vs Unsupervised.
- Choice of ML
- Supervised Learning
- Simple and Multiple Linear Regression, KNN, and more
- Linear Regression and Logistic Regression
- Theory of Linear regression, hands on with use cases
- K-Nearest Neighbour (KNN)
- Decision Tree
- Naïve Bayes Classifier
- Unsupervised Learning: K-Means Clustering
- Advanced Machine Learning Concepts
- Tuning with Hyper parameters
- Random Forest – Ensemble
- Ensemble Theory, Random Forest Tuning
- Support Vector Machine (SVM)
- Simple and Multiple Linear Regression, KNN
- Natural Language Processing (NLP)
- Text Processing with Vectorization, Sentiment Analysis with Text Blob, Twitter Sentiment Analysis
- Naïve Bayes Classifier
- Naïve Bayes for Text Classification, New Articles Tagging
- Artificial Neural Network (ANN)
- Basic ANN network for Regression and Classification
- TensorFlow Overview
- Deep Learning Intro
- Introduction to Deep learning
- What is Deep Learning?
- Various Deep Learning models in practice and applications
- Convolutional Neural Network CNN Intro
- Deep Dive into Optimizers, Activation Functions, Loss Functions, Back-Propagation
- RNN, LSTM, BERT, Attention based Neural Networks,
- Encoder & Decoder, Bi-Directional RNNs
- Transfer Learning, Different types of CNN Architectures
- Computer Vision Techniques – YOLO, FaceNet
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