Video Conference Details
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This Data Science course will help you gain expertise in Machine Learning Algorithms like K-Means
Clustering, Decision Trees, Random Forest, Naive Bayes using R. You'll learn the concepts of Statistics,
Time Series, Text Mining and an introduction to Deep Learning. You'll solve real life case studies on
Media, Healthcare, Social Media, Aviation, HR.
In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and
visualization taught alongside practical application oriented examples such as how to build a cloud data
science solution using Machine Learning platform, or with R, and Python on Azure stack.
- Explore the data science process
- Probability and statistics in data science
- Data exploration and visualization
- Data ingestion, cleansing, and transformation
- Introduction to machine learning
- The hands-on elements of this course leverage a combination of R, Python, and Machine Learning
- Python programming knowledge
- Basic machine learning knowledge (especially supervised learning)
- Basic statistics knowledge (mean, variance, standard deviation, etc.)
- Linear algebra (vectors, matrices, etc.)
- Calculus (differentiation, integration, partial derivatives, etc.)
- Data Preprocessing
- Linear And Logistic Regression Models.
- Decision Trees and Random Forest.
- Naive Bayes and Support Vector Machine.
- K-means and Hierarchical Clustering.
- Natural Language Processing.
- Artificial Neural Networks.
- Convolutional Neural Network.
Begin December 18 and end on January 18, 2018
Times: Every week, Monday and thursday 7 - 9 PM each day.
Each session will be recorded and the recordings will be shared after each session with students
1. There are no refunds.
2. If for any reason the course has not been taken, class is cancelled or rescheduled, the payment can be applied towards any future course by Omni212.
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