Data Science Online Training Curriculum
Our Data Science course is designed by expert trainers who hold in-depth expertise in various data science concepts and technologies. The online data science course designed by our experts covers the following topics in detail:
• Data Science Basics
This module covers topics like Data Science, significance, and R Programming fundamentals.
• Python Basics
The section covers Python data types, operators, Python Functions, and other concepts for Data Science.
• Data Structures
This module covers concepts like Data Structures, Data Manipulation, and Data Visualization.
• Data visualization
In this session, you learn about data visualization in detail with bar plots, ggplot 2, multivariate distribution, univariate analysis types of graphs, etc.
• Statistics
The basic statistics concepts like Correlation, Covariance, Probability, Classification, Data Sampling, Hypothesis, Binary Distribution, can be learnt in this module.
• Machine Learning basics
This discusses in detail Machine Learning fundamentals, linear regression, classification algorithms, supervised learning.
• Logistic Regression
You get to learn the logistic regression fundamentals, Poisson Regression, Multivariate Logistics Regression, Logistic models, etc.
• Random Forest and Decision Trees
In this module, you can learn classification, Decision Tree Induction, Random Forest Implementation, R Programming
• Unsupervised learning
This session discusses in detail the various clustering types, K-means clustering, historical clustering, and PCA in R-programming.
• Natural Language Processing
You can learn NLP, text mining, NPL with the data mining techniques, and Natural Language Toolkit (NLTK) in this section.
• Mathematics for Data Science
In this module, you can learn Probability, Correlation, Regression, Bayes Theorem, Conditional Probability, Sum rule, Product Rule, Joint Probabilities, Numpy mathematical functions.
• Scipy and Spark
You get to learn scientific computing with Scipy and the essential aspects of Python Integration with Spark
• Deep Learning and Artificial Intelligence
You can learn concepts of Neural Networks, supervised learning, deep learning, regression, classification, GPU, Machine Learning, Artificial Intelligence, multi-layer network, Time series modeling, clustering based on unsupervised learning, etc.
• Keras and TensorFlow API
In this module, you can learn the Keras and Tensorflow APIs to deploy deep learning and machine learning models.
• Big Data Technologies
You will learn about Hadoop, Hive, Scala, Kafka, MapReduce, Spark, etc, and Dstreams in this section in detail.
• Tableau
This section deals with the installation, architecture dashboards, graphs, and charts, associated with Tableau. You can also learn data blending, expressions, and tableau preparation.
• MongoDB
This section lets you master the learning concepts including MongoDB installation, MongoDB basics, Data Indexing, CRUD operations, Data Modeling, and Data Administration functions. You can also learn Data Security and Data Aggregation concepts.
• SAS
In this module, you can learn SAS analytic concepts such as functions, data sets, operators, graphs, procedures, and macros, and advanced SAS concepts.
• MS Excel
This module can teach logical functions, conditional formatting, pivot tables, data filtering, logical functions, and charts, with data analysis VBA concepts.