Data is the New Oil
Consumer behavior on social media and automated digital processes across business sectors are generating vast quantities of data 24x7. Powerful insights generated from this Big Data are a source of competitive advantage to the organizations who are able to invest in and use Data Science tools and technologies effectively. It is not surprising then to see that Data Science, Al, and ML skills are amongst the hottest disruptive skills in 2021 and beyond.
With the rapid proliferation of big data, companies are looking for data science professionals who are capable of uncovering business insights through data analysis and communicating those insights through succinct visualizations that help their companies make data-driven decisions.
Duration: 6 Months
Course Fee: As low as $8,500 USD
Most learners qualify for discounts or scholarships. Ask about options available to you!
Market Trends
- With the proliferation of the Internet of Things, the amount of data we generate continues to rise exponentially.
- Data will continue to almost double in size every two years if current trends continue.
- Consequently, jobs in big data and advanced analytics are in high demand.
Job Demand
Source: LinkedIn’s 2020 Emerging Jobs Report
Source: LinkedIn’s 2020 Emerging Jobs Report
Source: LinkedIn’s 2020 Emerging Jobs Report
Program Outline and Highlights
Data analysis using statistical techniques is a survival skill in data science. Initially, this program helps students build a strong data analysis foundation, with a special emphasis on using relevant statistical tools, and data visualization using various graphs, charts, and pivot tables in Excel. Students are then introduced to Python programming. They learn to use Python to write programs to do statistical analysis using libraries such as NumPy and Pandas. Further on, they learn to query relational databases, to process and manage data using ETL processes, create data models and visualize data using Tableau. Data modeling and data-based storytelling are two key aspects by which big data is leveraged for decision-making. Overall, students become competent at data analysis, visualization, modeling and forecasting, and communicating and collaborating with all stakeholders.
Student Guidelines
- Students must possess the curiosity and a determination to persist with demanding hands-on exercises and assignments.
- In addition, students need to fulfill the below
requirements:
- High School Diploma from an accredited institution
- Spoken and written English skills
- Appropriately configured PC with webcam and headset
- Uninterrupted internet connection
- Uninterrupted time to complete the learning activities on schedule
Delivery Guidelines
- Sessions will be conducted between 6:00PM – 10:00PM EST ON MONDAYS AND 6:00PM - 8:00PM EST ON THURSDAYS.
- Live online lectures on context-setting and concept building concepts
- 60% of the program is hands-on i.e. in each program, a student would spend over 60% of time on coding or hands-on activities
Who Should Attend?
Students who are keen on taking up a data analyst role or those looking for a career shift into big data analytics can take up this program. No prior programming or analytics experience is required to do this program - just curiosity and a determination to persist with the demanding hands-on exercises and assignments. Some other basic requirements are:
- High School Diploma from an accredited institution.
- Spoken and written English skills.
- Appropriately configured PC with webcam and headset.
- Uninterrupted internet connection.
- Uninterrupted time to complete the learning activities on schedule.
Exit Profile
This program delivers job-ready Data Science practitioners who can easily take up an entry-level role as a Data Analyst. Additionally, it sets them up for a future progression into the exciting new areas of Al and ML as Data Scientists or Data Engineers.
Our program gradually transforms students with no data analytics background into confident data analysts who can contribute effectively to data lifecycle activities such as data sourcing, data munging, wrangling and storage, data modeling and statistical analysis, data visualization, and data-based storytelling.
On successful completion of all the assignments and projects, each student will be able to:
- Analyze discrete data and structured data using Excel
- Apply descriptive and inferential statistical tools and techniques
- Summarize and represent data visually using graphs, charts, and pivot tables
- Create data dashboards using Excel
- Write Python programs using in-built data types, constructs, and standard libraries
- Use Pandas, NumPy for statistical analysis on large datasets
- Design and create data schemes for structured data
- Programmatically connect with RDBMS to retrieve, manipulate, and analyze data
- Slice and dice data to generate hypotheses
- Use statistical tools to validate a hypothesis
- Create advanced data dashboards & visualizations using Tableau
Program Coverage
Key Modules
- Data Analysis using Excel (Discrete and structured data, statistical tools, and techniques)
- Data Visualization using Excel (Data Visualization and Dashboarding)
- Python Programming (Solve problems using Python and its libraries)
- Data Analysis using Python (Pandas, NumPy, Intro to ML models)
- Data Processing and Management using RDBMS (SQL – DDL and DML to perform CRUD operations)
- Data Analysis using RDBMS and Python (Programmatically perform SQL queries, CRUD operations and “what-if” analysis)
- Data Processing and Management using ETL and Data Engineering
- Data Modelling (Data Analysis and Data Mining, Statistical Models)
- Data Visualization using Tableau
- Storytelling using Data
- Big Data Analytics (Classification, Clustering, and Regression, Social Media and Text Analysis)
Programs FAQs
Question 1:What is the tuition or cost for the program?
Question 2:Are there any scholarships available?
Yes! Our scholarship application requires only a few simple steps and may qualify you for a tuition reduction of up to 35% off standard pricing. Your program consultant can assist you throughout the application process and scholarship decisions are typically awarded within 2-3 business days.
Students who opt to forego scholarships can still receive a $1000 tuition discount if they elect to pay their tuition in advance of starting the program rather than financing their bootcamp. are eligible to receive a discount on the published tuition.
Question 3:How is my academic progress measured and monitored?
Question 4:What do I get at the completion of the program?
Question 5:When are the bootcamps currently scheduled to start?
Question 6:Can I keep working while studying in the program?
Question 7:How long does the program take to complete?
Question 8:Do you provide career planning support?
Question 9:How are you different from other programs I can join or other locations?
Question 10:What criteria do you look for in potential students applying to the program?
Question 11:How much time should I expect to dedicate to this program?
Our program requires you to participate in
- Four (4) hours of scheduled/live in-class lecture and guided lab session.
- Three (3) hours optional scheduled/live office hours for individual support.
- Two (2) hours of scheduled/Live in-class lab review.
- Additionally, three (3) to five (5) hours of time out of class is expected to be necessary to complete assignments and prepare for course assessments.
For a total expected time commitment of 12-15 hours per week.
Question 12:Do I need to possess an undergraduate degree to be eligible for the program?
Question 13:Do I need to have previous experience in information technology before enrolling in one of the virtual programs?
Question 14:Will I need to purchase books?
Question 15:Who are the faculty for the programs?
Question 16:Are the courses available online or in person?
Question 17:I’m an employer. How can I hire one of your students or become a hiring partner?
You can contact one of our Career Services professionals at auburnstudentsupport@stackroute.com
Question 18:Do I need my own computer?
You will need an appropriately configured PC with webcam, headset, and uninterrupted internet connection. Required specifications for your PC are as follows:
- To attend the program, students are expected to use their own computer and have an uninterrupted broadband internet connection.
- Hardware Requirements:
- Laptop/Desktop with Intel i5 (or later) with minimum 8 GB RAM (recommend 16 GB RAM).
- Minimum of 50+ GB Free HDD Space.
- Windows 10 (Patched with Latest Security Updates)
- HD Webcam.
- Audio enabled preferably with headset.
- Software Requirements:
- Google Chrome Browser.
- To join the virtual live sessions, students will need to download, and setup zoom client on their computer (one time setup) as required.
- For offline work, students will need to install zoom and join zoom channel with their registered email.
- From time to time, students may be required to install a few software updates during different parts of the program. Faculty will share the details during the respective stages of the program. The software needs may vary from program to program. These are mostly either open sources or evaluation version.
- For some of the programs, MS Office tools would be required. For example, Data Analytics program will require students to have MS Excel.
Question 19:Can I use Mac Book for the program?
Question 20:Can I use a Chrome Book or Tablet for my bootcamp?
Question 21:Do I need to purchase any application / software before starting the program?
Question 22:Can I use the free Excel version from Office 365?