Data Science Certified

  • Course Duration20
  • Course Start2020-09-01
  • Course Fee699.00 USD

Description

Interested in the field of Data science? Then this course is for you!

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

The Data Science with R programming training covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.

The Python Data Science Course teaches you to master the concepts of Python programming. Through this Python Data Science training, you will gain knowledge in data analysis, Machine Learning, data visualization, web scraping, and Natural Language Processing. Upon course completion, you will master the essential tools of Data Science with Python.

We will walk you step-by-step into the World of Data science. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time we dive deep into Data science. It is structured in following way:

  • Part 1 - Data Preprocessing
  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
  • Part 4 - Clustering: K-Means, Hierarchical Clustering
  • Part 5 - Association Rule Learning: Apriori, Eclat
  • Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
  • Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP
  • Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
  • Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA
  • Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

Who this course is for:
  • Anyone interested in Data Science.
  • Students who have at least high school knowledge in math and who want to start learning Data Science.
  • Any intermediate level people who know the basics of Data Science, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Data Science.
  • Any people who are not that comfortable with coding but who are interested in Data Science and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Data Science.
  • Any people who are not satisfied with their job and who want to become a Data Scientist.
  • Any people who want to create added value to their business by using powerful Data Science tools.

Curriculum

Key Features

FAQ

Yes. All of our courses follow respective body of knowledge for all courses. Also we have developed good practices and modification as per ongoing trends and requirements in projects. Our process are online , transparent , good practices being followed and trusted by recruiters as they get details of all successful students online on our portal. Thus all Diploma or Certification courses from IIRAMS (International Institute for Research in Agile and Management Studies) are globally accepted.

We understand everyone has different capabilities and responsibilities especially working professionals who have work loads apart from other responsibilities. Thus our programs are made accordingly to fit your schedule.  All diploma courses from IIRAMS vary from 6 month to one year based on mode of course selected.

Agile project management takes the ideas from Agile software development and applies them to project management. Agile methodologies generally promote a project management process that encourages stakeholder involvement, feedback, objective metrics and effective controls.