Advanced Data Analytics
Ready to start your career in Data Analytics?
This course will take a deep dive into how to use data to drive powerful and informed decisions. You will learn how to acquire data from various sources, visualize data in a meaningful way, do exploratory analysis to understand data and its quality, perform classification of data to predict/forecast what might happen in the future, and optimize decision making tell an impactful story. Data is considered as new gold, and data scientists are the new gold miners. Learn the skills you need for this hottest job of our time. This 12-week hands-on course will take you an an end-to-end journey in data science career.
Ready to reinvent yourself and become a data scientist? Please fill out an application so that we can learn more about you and determine if this course is the best fit for you and your goals. As soon as we receive your application, we’ll be in contact. Get started.
In our Bellevue Data Science course, we follow the Gartner model of Data Analytics. Learn an overview of the various data jobs and where data science stands in the industry.
Learn Python programming, Machine Learning, Statistics and Regression, how to acquire data from various sources, how to visualize data in meaningful way, how to do exploratory analysis to get an understand of the data and its quality and perform classification of data. Use prescriptive and predictive analysis to create forecasting models about what might happen in the future, how to optimize decision making and how to tell an impactful data story. You will also get tips on advancing your career in the data science field.
Market research on the field:
- #1 in the List of Best Jobs in America
- #1 in the List of 25 Jobs with Work-Life Balance
- The 10 Hardest Jobs to Fill Right Now
- Harvard Business Review calls it sexiest job of 21st century
- 190,000 predicted shortage in Data Scientists by 2018
Jobs for data scientist:
|Introduction||Overview||Analytics in Decision Making|
Maturity model Setup with tools. Introduction to Python Demo & Lab
|Descriptive||Data Acquisition, Data Profiling||Sources of Data|
Data storage and Acquisition
Data Quality Framework
Data Profiling, Continue learning Python, Introduction to Azure ML, Demo & Lab
|Descriptive||Visualization||Introduction to visualization|
Tools & Techniques for Visualization
Demo using Power BI & Lab
Introduction to Statistics
Univariate & Bivariate Distributions
Demo & Lab
Introduction to Real-Time Stream Analytics
Demo & Lab: Creating end to end stream analytics pipeline and visualization
|Predictive||Simple Linear Regression||Introduction to Regression|
Demo using Excel & Python & Lab
|Predictive||Multiple Linear Regression||Multiple Linear Regression|
Estimation of Regression Parameters and Model Diagnostics
Dummy, Derived & Interaction Variables
Demo using Python & Lab
|Predictive||Logistic Regression||Logistic Regression|
Estimation of Parameters and Model Diagnostics
Logistic Model Deployment
Demo using Python & Lab
Support Vector Machine
|Introduction to Decision Trees|
Classification and Regression Tree (CART)
Naive Bayes Classification Support Vector Machine
Neural Network Demo & Lab
Demo & Lab
|Predictive||Forecasting and Time series Analysis||Forecasting|
Time Series Analysis
Auto-regressive Integrated Moving Average (ARIMA)
Forecasting Accuracy, Demo & Lab
|Introduction to Linear/Integer/Network model|
Demo of Linear/Integer/Network Model Building
Introduction to Simulation
Demo & Lab Discussion of resources available & Next step forward
|Start Date||Deadline to Enroll||Tuition||Enrollment Status</th|
|Sept. 17th, 2020||Sept. 10th, 2020||$4000||Open|
Thursdays – 6pm – 9pm
2265 116th Ave NE, Ste 200
Bellevue, WA 98004
Do I need programming experience for this course?
While knowledge of programming is helpful, it is not mandatory for this course. We will cover R/Python as part of the course. As long as you bring lot of passion to learn, can follow basic algebraic concepts, have some literacy in computer tools like Excel and work hard, you should be fine.
Do I need statistics knowledge for this course?
We will teach you any statistics concepts needed as part of the course.
Who should take this course?
The course is designed for diverse backgrounds; however, our Intro to Data Analytics course is highly recommended if you don’t have knowledge or experience with the basics of Excel, SQL, and Power BI used in data analytics. If this is a field you really want to learn, you can sign-up for the course whether you are software engineer, product/program manager, analyst, researcher, consultant, statistician, student etc. We will adjust the approach based on the attendees.
How much time do I need to spend outside of classroom?
It can vary depending on your unique background. However, it usually takes 3-6 hours/week outside of the classroom for homework and study time.
What types of problems we will be solving as part of the course?
The business problems for demo, labs and homework will be taken from a wide variety of industries representing practical problems.
Would I become a data scientist after finishing the course? How can I transition to ‘Data Science’ career?
We cannot promise that you will become a data scientist with a 36 hours course. It depends on how well you are able to analyze and use the data you have in front of you. This course is jam packed with topics starting from basic to advanced data science topics and follows the Gartner Maturity Model for Analytics. We will show you some potential paths to a career in Data Analytics or Data Science based on your personal abilities and accomplishments.
Will I be given a certificate after the completion of the course?
Yes, you will be given a certificate of completion for this course after you pass your final exam.
More FAQ available here.