With the rapid proliferation of big data, companies are looking for data science professionals who would derive business insights from data, communicate them through succinct visualizations and thereby drive data-driven decision making. 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 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 deriving business insights through data analysis and communicating those insights through succinct visualizations, thereby helping their companies make data-driven decisions.
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 Data
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
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 fulfil 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
Students must possess the curiosity and a determination to persist with the demanding hands-on exercises and assignments.
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
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.
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
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)
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.
Yes, we offer students career support and coaching throughout the duration of the program. Students have an opportunity to develop a close working relationship with a career advisor to discuss resume building, job sourcing, interview techniques, salary negotiations and more.
We believe the main criterion for success in our program 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 20 -24 hours per week).
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.
Our program requires you to participate in four (4) hours of scheduled/live in-class sessions, three (3) separate days per week (for example, Tuesday, Thursday and Saturday live class sessions). Additionally, eight (8) to twelve (12) 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 20 -24 hours per week.
What makes our program different is our extensive relationships with leading global companies that hire information technology professionals. Our decades long relationships with these global leaders provides us with unmatched insight and understanding of the specific skills that these employers are demanding as part of their digital transformation efforts. Working with our partners, we built our programs to embed these mission critical skills and abilities into our programs so that students who successfully complete the program are job ready, day-one, with the skills and abilities that are in high demand in today’s technology-focused workforce.
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 will have as a working professional in the information technology sector. The objective of our faculty and our programs is for you to be job ready on day one of your new career.
Courses are available 100% virtually with live online sessions occurring three (3) days per week. You are expected to attend all of the live sessions in the program in order to be successful. In the rare instance where you simply are unable to attend one of the live sessions, we record them and make them available to you after the live session is completed.
Yes, 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.
NOTE: These bootcamps are designed to prepare students for new or advanced careers in the selected field. Candidates who complete this course will receive a Certificate of Completion from Auburn University. While students who complete this program will have obtained the required skills and instruction necessary to sit for the relevant national certification exam associated with the selected course of study, these bootcamps are not designed to be exam-prep courses.
