This learning path is designed for a professional taking his first steps in the world of analytics and wishes to develop
skills in both big data and data science. It is important to be a multi-skilled expert to make it big in the field
of analytics to be able to adapt to the fast changing trends of the industry.
About the program
What are the course objectives?
Expertize in the field of data science starts with apprehending and working with the core technology frameworks to
analyze big data. Participants will experience in developmental and programming frameworks. Hadoop and Spark are used
to process immense amounts of data in a distributed computing environment, and build experience in complicated data
science algorithms and its implementations with the help of R programming language, the most-sought language for
statistical processing. The insights obtained from the data by the participants are represented as consumable reports
using data visualization platforms like Tableau.
Once participants get experienced in data management and predictive analytic techniques, they will have clear transparency
on state-of-the-art machine learning technologies. This expensive learning path will help participants to improve
around the comprehend spectrum of big data and data science technologies and techniques.
What skills will you learn?
This is an comprehend course for big-data and data science aspirants. It contains all vital technologies in big data,
data science and reporting and even visualization. This program is structured to enrich participant potentiality at
every step, so it was recommended that participants follow the learning path as it is suggested to assure a smooth
transition till the end of the program. The learning path is as follows:
| Step |
Training |
Objective |
| 1 |
Data Science with R |
This course trains participants in the R programming language and essential statistical and predictive analytics concepts. |
| 2 |
Big Data Hadoop and Spark Developer |
This course allows participants to expertise in different components of Hadoop ecosystem like Hadoop 2.7, MapReduce, Yarn, Pig, Hive, HBase, Impala, Sqoop, Flume and Apache Spark. The course is aligned to Cloudera CCA175 certification. |
| 3 |
Tableau Desktop Associate training |
This course help participants to expertise in the different aspects of Tableau desktop and building visualization, organizing data and designing dashboards, it helps participants to prepare for the Tableau Desktop Qualified Associate certification. |
| 4 |
Data Science with Python |
This training presents the different packages in Python like NumPy, SciPy, Pandas, and Scikit-learn for performing data analysis. |
| 5 |
Machine Learning |
The course helps participants to get an apprehending of Machine Learning applications and algorithms. It also consists deep learning and Spark Machine learning. |
Why should I take this master’s program?
an expert in this field, participants need to have a working experience of the three important pillars in the analytics
ecosystem: data management, data science and visualization and reporting. This master’s program will improve participants skills in:
Big Data
Big data management is the competency to store and evaluate huge amounts of unstructured data. Now, we have an overflow
of online information, many companies have chosen big data practices to handle these immense data volumes. Hadoop offers
the distributed file system for storage, and MapReduce programming in Java is used for the processing. In lifecycle
of analytics, it is important to be capable to store and query data to keep the required algorithms.
Data Science
Data Science algorithms use data to establish insights. Once participants have an effective way to optimize data, they
can use historical data for both descriptive and predictive analytics. This can be accomplished through a programming
language like R or Python, which contain libraries for statistical analysis. Learning these languages are important to
create custom models for analytics, which is a major expectation for any data scientist. These skills start from
fundamental probability to enhanced machine learning.
Reporting and Visualization
Once participants have insights about the data, it is crucial to make the insights available to the organization using
visualization and reporting.
This program also contains a number of electives to assure participants to get knowledge of the comprehend ecosystem and
complementary skills in these fields. This two-year period assures participants have enough time to maximize, develop
skills and implement them in real world scenarios.
What is CloudLab offered by 4CLearn?
CloudLab is a cloud-related Hadoop environment designed to assure error-free execution of all experiential project
work. CloudLab is a pre-configured Hadoop setup so participants will avoid potential defects that can raise during
set up of a virtual machine, like:
- Installation and system compatibility issues.
- Difficulties in configuring systems.
- Issues with rights and permissions.
- Network slowdown and failure.
- Single machine capacity instead of clusters.
CloudLab projects will be implemented on cloud- related Hadoop clusters running on Hadoop 2.711.
Participants can access CloudLab from 4CLearn’s Learning Management System (LMS). We have lab environments for R and Python and provides participants with seamless access.
Who can take this program?
Many roles are profitable from this program and achieve new career opportunities with high salaries, including:
- Software developers and testers
- Software architects
- Analytics professionals
- Business analysts
- Data analysts
- Data management professionals
- Data warehouse professionals
- Project managers
- Mainframe professionals
- Interested graduates to create a career in analytics
How do I earn the Integrated Program in Big Data and Data Science certification?
Once participant has finished the courses in the learning path and earned their individual certificates, they will
receive the certification for the integrated program in Big Data and Data Science from 4CLearn.
Participants have to:
- Finish the course-end assessments.
- Deliver their project and clear the examination for each course.
These criteria must be satisfy for each of the five courses in the learning path.
FAQs
How do I enroll in the master’s program?
Participants can register for this program on our website and can use an online payment using any of the following options:
- Visa Credit or Debit Card
- MasterCard
- American Express
- Diner’s Club
- PayPal
Once course payment is received participant will receive a automated payment receipt and access information through email.
What can I expect from the master’s program?
Participants will have access to E-learning content for all courses involved in the learning path, exclusive forums
decreased by faculty and industry experts, and also regular mentoring sessions by faculty and industry experts. After
finishing the requirements for the program, participants will receive the Master’s certification for the Integrated
Program in Big Data and Data Science.
Are there any limitations? Where and how can I get access for the e-learning content?
Participants should register for the course by paying the course fee, they will have regular access to the e-learning
content on our website. An course purchase email will be automated to guide the participants through the process.