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Introduction to Data Science

Mon Thru Fri (1 Week)
EST:[09:30-13:30]
IST:[20:00-00:00]
US $1499

Join On Premises at Parsippany Or Online

This course lays a foundation for those aspiring to enter the world of data analytics, reporting and data science. It explains in a scientific manner the most essential concepts and tools required for understanding and demonstrating mathematical principles and theoretical concepts behind data analysis. "Data Scientist" has become a popular occupation with Harvard Business Review calling it "The Sexiest Job of the 21st Century". Data Science has recently created waves throughout the corporate world on account of recent advances made in Big Data Analytics, Statistics, Data mining, predictive and prescriptive analytics.

About this Course

Mon Thru Fri (1 Week)
EST:[09:30-13:30]
IST:[20:00-00:00]
US $1499

Join On Premises at Parsippany Or Online

This course lays a foundation for those aspiring to enter the world of data analytics, reporting and data science. It explains in a scientific manner the most essential concepts and tools required for understanding and demonstrating mathematical principles and theoretical concepts behind data analysis. "Data Scientist" has become a popular occupation with Harvard Business Review calling it "The Sexiest Job of the 21st Century". Data Science has recently created waves throughout the corporate world on account of recent advances made in Big Data Analytics, Statistics, Data mining, predictive and prescriptive analytics.

Course Syllabus

  • Topic 1: Introduction to Data Science
This chapter introduces the field of data science and teaches basic concepts of data analysis and statistics; and presents an overview of the various types of statistics: Descriptive and Inferential. We also take a close look at the components of these branches, and perform estimation, modelling, data visualizing and summarizing.

  • Topic 2: Descriptive Statistics
Understand data visualization though different types of charts, tables, frequencies and variables. Learn how to summarize a given dataset by using descriptive techniques of computing Mean, Median, Mode, Variance, Standard Deviation etc. Study properties like skewness, kurtosis, peakedness, and perform outlier identification. Learn types of bivariate numerical data, bivariate outliers and Simpson’s paradox.

  • Topic 3: Probability Theory
Understand how to apply concepts of Probability, Law of Large numbers, Events and Laws of Probability with applied examples of outcomes. Learn the differences between independent, complementary, disjoint and conjoint events, and the popular Bayes’ theorem.

  • Topic 4: Random Variables and Distribution
Understand how to apply and use random and discrete variables, and probability distribution. Construct a probability distribution using techniques like Sampling and Central Limit Theorem. We cover all of the major continuous distributions, including, uniform, exponential, beta and gamma distributions. Discrete distributions make up the latter half, and include Bernoulli distribution, Binomial, Poisson, Geometric, Negative Binomial and Hypergeometric distribution.

  • Topic 5: Inferential Statistics
Learn how to use standard techniques of estimation and hypothesis testing to determine the probability whether a given hypothesis is true or not and to draw meaningful inferences out of a dataset. Topics include:  confidence intervals, point and interval estimations, p-hacking, null and alternate hypothesis, type I and II errors, and levels of significance.

  • Topic 6: Cluster Analysis
Understand the methods used for Cluster Analysis, analyze different types of clusters (hierarchial, partitioned, exclusive, overlapping and fuzzy) and learn about methods used to analyze a cluster in a given dataset. Methods include the use of K-Means for clustering, agglomerative hierarchial clustering and DBSCAN.

  • Topic 7: Regression Analysis
Learn about types of regression models (simple and multiple) and methods of analyzing certain models by logistic regression, and by determination of coefficient, R-squared. Study the Bootstrap in statistics by learning degression and goodness of fit, and the Least Squares Model.

  • Topic 8: Tests in Statistics
Chi –square test, Anova (Analysis of Variance), and parametric, non-parametric tests. Study variance through both the One Way Anova and F-Distribution.

  • Topic 9: Time Series Analysis
Methods for analyzing time series data. We describe the Holt-Winter model of exponential smoothing, go over the effect of smoothing on a dataset, and compare various smoothing models like ETS and ARIMA against Holt Winter’s. Learn the differences between seasonality and stationarity, and cyclical analysis of a time series.

  • Topic 10: Special Topics
Miscellaneous topics covering advanced methods of analysis: e.g. Factor Analysis, Machine Learning, K-nearest neighbors and Gradient Descent.

Course Structure

The course is structured into four four-hour sessions. 

Session 1
Chapters 1-3
Introduction to Data Science
Descriptive Statistics
Probability Theory
Session 2
Chapters 4-6
Random Variables and Distribution
Inferential Statistics
Cluster Analysis
Session 3
Chapters 7-8
Regression Analysis
Tests in Statistics
Session 4
Chapters 9-10
Time Series Analysis
Special Topics
Conclusion


Course Logistics

How the course is delivered:

An instructor delivers the course live over the Internet. Students have two choices to join the lectures:

  1. Join the lecture from home
  2. Join the lecture at our facility at Parsippany, New Jersey

Additional Charges may apply for the classes at our facility.

If you prefer joining the lecture from our facility, you must book a spot at the facility two weeks before the start of the course. You may do so by using the email or phone or live chat provided on our home page. Make sure you have a confirmation email from us for your booking before you arrive at the facility. After receiving a confirmation, you may arrive at the facility with or without a laptop. Ask for Net Serpents education center at the front desk.

If your course is not scheduled between 8 am and 5 PM EST on weekdays or falls on a weekend, a member from our staff will meet you at the building entrance and escort you in as special permission is required outside regular hours of operation.


Steps to join the lecture from home:

  1. If you haven’t done so already, create an account by clicking on Register on top right of home page
  2. Login with your user-id and password and click Enroll Now on the course card in the home page. Click Enroll Now again in the pop-up window. You will navigate to the course order page. Apply a discount code if you have one and then click on Place Order. Fill in the requested credit card and personal details. These are not saved to our database. Your payment is safe and authorized by a secure payment gateway authorize.net.
  3. On successful payment you will receive a confirmation email
  4. On the scheduled date and time of the course, go to hadoopexpress.com and login with your user-id and password
  5. You will see your username on top right. Click on it and go to your dashboard by selecting My Dashboard
  6. In your dashboard page click the Go to course button
  7. Click on Go to live class on right hand side of page
  8. You will land on a Zoom meeting page where you will be able to download zoom and join the meeting. The download is required only the first time
  9. You will be able to see the instructor screen and pick the option to use your phone or computer for sound. Make sure you have a microphone and speaker on your laptop or a headset connected to it.


Steps to join the lecture from our facility:

  1. Create an account and enroll by paying for course
  2. If you haven’t done so already, create an account by clicking on Register on top right of home page
  3. Login with your user-id and password and click Enroll Now on the course card in the home page. Click Enroll Now again in the pop-up window. You will navigate to the course order page. Apply a discount code if you have one and then click on Place Order. Fill in the requested credit card and personal details. Note: we don’t store these details in our database. Your payment is safe and authorized by a secure payment gateway authorize.net.
  4. On successful payment you will receive a confirmation email.
  5. Call or email or use live chat at our home page at least two weeks in advance of the start date to request and confirm your reservation at the facility.
  6. On the scheduled date and time of the course, arrive at our sponsoring facility Net Serpents LLC, 2001 Route 46, Suite 310, Waterview Plaza, Parsippany, NJ 07054. You will be provided a seating space with all necessary equipment to attend the lecture. You may bring your laptop or request a computer from us. Please call for additional details.

The course is delivered over four live sessions of 4 hours each. Each live session is also recorded and made available in your dashboard over the internet for reviewing the lecture afterwards at your convenience. Further, you may download student guides, examples, exercises and videos to your laptop for personal use.

If the software does not require purchasing a license, you may install it on your laptop with guidance from our instructor. If you are unable to do so for any reason, you may request accessing the software provided by us on the cloud.


Discussion Forum:

A discussion forum is available on-line to allow students to post any queries or discuss any topic with other students or the instructor.


Course Material and Videos

Each live session is also recorded and made available in your dashboard over the internet for reviewing the lecture afterwards at your convenience.Further, you may download student guides, examples, exercises and videos to your laptop for personal use. Course material and discussion forum may be disabled anytime one month after the delivery of the last lecture.

Opportunities after the course

Data Science is fast becoming must-have knowledge for all professionals in today’s corporate work force. The Big Data revolution and rising jobs in data analytics means that workers today must understand the fundamentals of data science. 

At the completion of this course, you will be perfectly equipped to pursue other courses in our Data Science track, going on to apply these concepts in R Studio by learning R Programming, or using SAS and other such powerful robust tools to draw meaningful conclusions from data.

By undertaking this course you will develop an analytical ability to find and interpret rich data sources, analyze large datasets and create visualizations and mathematical models to present and communicate data insights and findings that are sometimes startling and eye-opening. The course is a “must-have” for any person endeavoring to be a data analyst, BI programmer, statistician, data manager or data scientist. Programmers and report writers that use tools like R, SAS, Business Objects, OBIEE, Tableau etc. will be specially benefitted as they would get an insight into business requirements that are spelled out by data scientists within a company.

Sessions

ET:[9:00-01:30] Mon Thru Fri

Delivery Method
Instructor Based $ 1499

Course at a Glance
  • English
  • Skill Level: Intermediate
Online Classes
Assignments: 1
Project: 0
Lifetime Access
Certificates
System Requirements

For On premise courses, you may bring your own laptop or use the one provided in the classroom. If you intend to use the one provided in the class, please let us know one week in advance of the course start date.

 

Prerequisites
  • None. Basic computer literacy is expected as well as high school or higher graduation.

Testimonials

" The course was very interactive and easy to understand even for a beginner like me! It helped me prepare and pass my certification soon after completing the course!! "

- Priyam

" I really loved this course. It was fast paced, very hands on with fun filled exercises. Not only do I have lifetime access to lectures and notes, I can also email the instructor any time for help! Awesome!! "

- Samuel Adlekha

" Loved the the course. The instructor was patient and provided great demos and examples. I am new to programming but felt so comfortable since it was well explained. Awesome! "

- Shveta

" It was a pleasure and great learning experience with Net Serpents under the guidance of Mr. Shashi Prakash. "

- Aijaz

Contact Us:

Hadoop is a registered trademark of the Apache Software Foundation(ASF) and Hadoop is a product owned by Apache. Hadoop Express is not affiliated in any way to ASF . All educational material, resources, videos and other content available on this site is created and owned by Net Serpents and is intended only to provide training. This website does not own any of the products on which it provides training, many of which are owned by Apache while others are owned companies such as SAS, Python and Oracle. Net Serpents LLC is committed to education and online learning. All recognizable terms, names of software, tools, programming languages that appear on this site belong to the respective copyright and/or trademark owners.