About the Program
As rightly said by Max Levchin, Co-Founder of PayPal
“The world is now awash in data and we can see consumers in a lot of clearer ways.”
Data analytics is becoming the master key for opening the path of success and growth of businesses, irrespective of their Tech or Non-Tech nature. Companies are using data analytics to make better business decisions by analyzing customer trends, which in turn is maximizing the customer satisfaction ratio.
Based on this market understanding and the employment opportunities in the IT sector, EduBridge has designed a full-time certification program for you on Data Analytics. This program is driven by a group of highly qualified and experienced master trainers from the Data Analytics spectrum, who will inculcate a strong technical foreground and assist you to get your dream job through a dedicated placement manager forum.
This course will well-equip you with Data Analytics tools like Python, R, SAS, Excel, VBA, Tableau along with an introductory idea of Machine Learning and its Algorithms. Project-based and experiential training techniques adopted for the delivery of the program, will make you more robust and give you hands-on experience. Our “Live Online Sessions” will ensure 100% access and constant connection with the master trainer during your training program.
This course will,
- Help you to become a master in Data Analytics with Excel, R, and Python, which are highly recommended open source languages
- Enhance your knowledge in SAS, which is the most widely used Software for Analytics
- Assist you in using the VBA programming language effectively
- Guide you to use Tableau in analytics, which is one of the most in-demand data visualization tools
- Introduce you to Machine Learning with Python and build projects like E-mail Spam classifiers, Churning Inbox and Noise removal from images along with a capstone project based on the dashboard.
We hope that you will gain the required knowledge from this program and demonstrate the skills learnt.
All the best!
After completion of this module learners will be able to describe and discuss the key terminology, concepts tools, and techniques used in business statistical analysis They can also compare the descriptive and inferential statistics. They will understand the importance of probability theory in the design and development of machine learning algorithms.
After completion of this module, learners will be able to define data analytics and describe types of data analytics. They will also be able to select the most suitable analytics method from prescriptive and descriptive depending upon the problem statement requirement.
Interdisciplinary Group Formation
After completion of this module learners will be able to write, evaluate and execute python programs.
After completion of this module, learners will be able to use advanced python libraries NumPy and Pandas to perform statistical analysis of data. They will also learn to use these libraries to perform data cleaning, wrangling, and visualisation operation.
After completion of this module learners will be able to write, evaluate and execute simple R programs for statistical analysis of data. Learner will also learn to perform mathematical operations with the help of R and understand the strength of R language in performing mathematical calculations
After completion of this module learners will study predictive analytics with the help of case studies and analyze their implementation using R language.
Methodology and Implementation
After completion of this module learners will be able to differentiate between supervised and unsupervised machine learning. They will also learn to select appropriate machine learning algorithm as per the problem statement and data set used
After completion of this module, learners will be able to implement machine learning algorithms They can also use data sets for implementation of machine learning algorithms.
After completion of this module learners will be able to use Excel for data analysis. Learners will also get an overview of EXCEL analytics and will learn to develop visualisation with EXCEL
After completion of this module learners will be able to create and edit macros by writing VBA code in the VBEThey will also learn to Build user-defined functions in Excel.
After completion of this module learners will be able to use SAS studio for data analytics
Results and Conclusion
After completion of this module learners will be able to use Tableau as a data visualisation platform. They will be able to design, develop and demonstrate created visualisation.
Demo and viva voce
In this module, trainer will conduct Mock Interview for students. Trainers to also share the tips for technical interviews.
EduBridge’s programs are designed to offer learners a pathway to placements and its certificate is an official credential for the learners.
On satisfying the attendance criteria requisite and by successfully clearing the assessments with a 50% score and above, learners will be awarded a Certificate of Achievement.
Learners who are unable to clear all the assessments and have scored less than 50% but fulfilled the attendance criteria will be awarded a Certificate of Completion.
Though not mandatory, it is beneficial to have basic coding skills when learning or working as a Data Analytics professional.
Yes. The course offers real time coding problems and assessments that will help the learners get an hands-on-experience of the course contents and help them master the various concepts of Data Analytics
The tasks of Data Analytics involve providing operational insights into complex business situations. This also predicts the upcoming opportunities which the organization can exploit. Data Science is a field that contains various tools and algorithms for gaining useful insights from raw data. It involves various methods for data modeling and other data-related tasks such as data cleansing, preprocessing, analysis, etc. Big Data implies the large amount of data which can be structured, unstructured and semi-structured generated through various channels and organizations
Yes, you can sign-up for the Data Analytics course even if you do not come from a technical background. However, having basic knowledge of programming languages and mathematics would be beneficial.
Yes. This Data Analytics course will teach you the fundamentals of programming languages, statistics, and industry standard techniques from scratch to build up your foundational knowledge and enhance your analytics career journey.
Data is ruling businesses around the world. The more data-driven you’re, the more beneficial it is for your organization. By taking insights from data, you can make meaningful decisions, plan strategies, and help your business achieve its goal faster. Enrolling in this extensive Data Analytics course is definitely going to be an advantage.
R, SAS, Python, and Apache Spark with Scala are the predominant languages used by Data Scientists and Data Analysts. Tableau, Excel, and QlikView are the most popular and effective analytics tools.
Data Analytics is a discipline focused on extracting insights from data, including the analysis, collection, organization, and storage of data, as well as the tools and techniques used to do so. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.
Data Analysis is the process of cleaning, transforming, and modeling data to find meaningful insights and make better decisions. In contrast, Data Analytics is a broad term that involves many diverse types of data analysis.
A Bachelor’s degree, preferably in Mathematics, Statistics, Computer Science, or related fields is with a minimum of 50% (or higher) if required for anyone to enroll in this course. Being familiar with Statistics, core Math concepts, programming basics (Python, R, or Java), and Linux fundamentals would be an added advantage.
The following topics will be covered in this course : - Core Python & Advanced Python - Advanced Excel - R Programming - SAS - Tableau - Statistics
Excel is used in data analysis because it’s easy to learn and use. Its functions like vlookup, xlookup, pivot table, analysis tool pack make it the most widely used tool by any analyst position like data analyst, business analyst, business intelligence analyst.
R in data analytics is used to handle, store and analyze data As a programming language, R provides objects, operators, and functions that allow users to explore, model, and visualize data. It can be used for data analysis and statistical modeling.
Organizations view Data Analysis as one of the most crucial job specialties due to the value that can be derived from data. Data is more abundant and accessible than ever in today’s business environment. In fact, 2.5 quintillion bytes of data are created each day. With an ever-increasing skill gap in Data Analytics, the value of Data Analysts is continuing to grow, creating new jobs, and career advancement opportunities. By 2022, the World Economic Forum predicts that Data Analysts will be one of the top emerging jobs.
Tableau is a powerful and versatile data analytics and visualization tool. Its drag-and-drop interface makes it easy to sort, compare, and analyze data from multiple sources, including Excel, SQL Server, and cloud-based data repositories.