Need For The Program
Create and interpret statistical summaries and data visualizations that support understanding and guide decision making. Use data and key performance indicators to build a dashboard that uses visuals to improve your understanding of complex business situations Formulate a business question as a scientific hypothesis that can be tested using statistical methods. Create and validate regression models that can be used to determine the effect of attributes on a decision and predict likely outcomes Use data to describe and reduce uncertainty in decision making.
- Help people and organizations create visualizations that make sense and weave them into compelling, action-inspiring stories.
- Learn the essentials of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story.
- Learn how statistics plays a central role in the data science approach.
- This module will pave the statistical foundation for the later modules on data science.
- You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.
- Anova for hypothesis testing
- This course will teach you how to program in R and use it for effective data analysis.
- It also covers reading data into R, accessing R packages, writing R functions, debugging and commenting R code
- You will also learn how to handle complex data, build R packages and develop custom data visualizations
- Learn how to Program and Analyze Data with Python.
- Begin with the foundational programming concepts including data structures, networked application program interfaces, and databases using Python and progress to visualization with a focus on reporting, charting and using the matplotlib library.
- Seaborn: Seaborn is a Python data visualization library based on matplotlib. Creating advance Graphs like text and MAP
- The topics covered in the course include supervised learning, best practices, and innovation in ML and AI, while you also get to encounter numerous case studies.
- Learn to make accurate predictions, build a great intuition of many machine learning models, handle specific tools like reinforcement learning, and NLP.
- Most importantly it teaches you to choose the right model for each type of problem.
- Cost Function, Gradient Decent
- Model Selection ARIMA: An ARIMA model is a class of statistical models for analyzing and forecasting time series data.
- It covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume and Sqoop.
- Throughout this online instructor-led Hadoop Training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism and Finance domains
- Introduction to SQL
- Learn about the techniques of Deep Learning, know how to build neural networks and implement a range of machine learning projects.
- There will be real time case studies including sign language reading, music generation and natural language processing among others. Along with all the concepts, you will be taught to implement these concepts in Python and Tensor Flow.
How It works
Live Online Sessions
Each session is interactive and informative, featuring case studies, quizzes, and projects.
Training 5 or more people?
We provide custom courses and group sessions as well. To know more about our Customized Programs.
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