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Data Analytics

With the rapid proliferation of big data, many companies are looking for data science professionals who can idenitify business insights from data, communicate through succinct visualizations and drive data-driven decision making. This bootcamp can help students begin to prepare for an entry-level role as a Data Analyst. Additionally, it can set them up for a future progression into the exciting areas of AI and ML as Data Scientists or Data Engineers.

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: 5 Months

Course Fee: $ 10,500

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

37%Year on Year growth for Data Scientists.

Source: LinkedIn’s 2020 Emerging Jobs Report

33% Year on Year growth for Data Engineers.

Source: LinkedIn’s 2020 Emerging Jobs Report

74% Year on Year growth for Specialist AI Engineers.

Source: LinkedIn’s 2020 Emerging Jobs Report

overview

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 the 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 1What do I get at the completion of the program?

Answers

You will receive a Certificate of Completion from UNH Professional Development & Training.

Question 2When are the bootcamps currently scheduled to start?

Answers

Cohorts in each of the various virtual program tracks (Data Analytics, Cloud Systems Administration) typically start every month. Please call 603-769-3409 to get more details

Question 3Can I keep working while studying in the program?

Answers

Yes, our virtual programs are designed specifically to address the challenges of individuals who are employed but actively pursuing a career change or advancement in their existing field. The part-time schedule allows you to continue working or pursue other interests, while advancing your skills through your active participation in the program.

Question 4How long does the program take to complete?

Answers

Students are expected to complete the program in 6 – 7 months depending on the program.

Question 5What is the tuition or cost for the program?

Answers

The cost of the program is $ 10,500

Question 6Do you provide career planning support?

Answers

Yes, we offer students career support and coaching throughout the duration of the program. Students have an opportunity to develop a working relationship with a career advisor to discuss resume building, job sourcing, interview techniques and salary negotiations.

Question 7How are you different from other programs I can join or other locations?

Answers

What makes our bootcamp different is our extensive relationships with leading global companies that hire information technology professionals. Our decades long relationships with global companies provides us with insight and understanding of the specific skills that many employers are demanding as part of their digital transformation efforts. Working with companies, we built our programs to embed these mission critical skills and abilities into our programs so that students who successfully complete the program can be prepared for many entry level jobs in today’s technology-focused workforce.

Question 8What criteria do you look for in potential students applying to the program?

Answers

We believe the main criteria for success in our bootcamp is your effort and determination to succeed, as well as time. You will need to be prepared to dedicate the necessary time to the program in order to be successful (typically between 10-12 hours per week)

Question 9Do I need to possess an undergraduate degree to be eligible for the program?

Answers

No. You are required to possess a High School Diploma from an accredited institution or a GED, as well as being proficient in spoken and written English.

Question 10How much time should I expect to dedicate to this program?

Answers

Our program requires you to participate in two (2) live sessions per week. Each session could be 2–4-hour duration. Additionally, you will be expected to spend 6 hours completing assignments and labs. The instructor will also schedule non mandatory office hours for additional academic support if you require

Question 11Do I need to have previous experience in information technology before enrolling in one of the virtual programs?

Answers

No specific experience is needed as long as you are determined and eager to learn.

Question 12Will I need to purchase books?

Answers

All materials and access to virtual labs and other learning environment will be provided to you and are included in the tuition/cost of the bootcamp.

Question 13Are there any scholarships available?

Answers

Students who elect to pay their tuition in advance of starting the program are eligible to receive a discount on the published tuition.

Question 14Who are the faculty for the programs?

Answers

Our faculty (Lead Mentors/Instructors) are typically working professionals who are subject matter experts in their field. They are encouraged to bring real-world experience and situations into our classrooms to expose our students to projects and challenges that replicate the experiences you may have as a working professional in the information technology sector.

Question 15Are the courses available online or in person?

Answers

Courses are available 100% virtually with live online sessions.

Question 16I’m an employer. How can I hire one of your students or become a hiring partner?

Answers

You can contact one of our Career Services professionals at unhstudentsupport@stackroute.com

Question 17Do I need my own computer?

Answers

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) and/or Ubuntu OS (Can be used as a Dual Boot).
    • 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 a light client on their computer (one time setup) as required.
    • For offline work, students will need to install Slack on their computer and cell phone.
    • 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.