Top Data Analytics Courses Offered By Masai With Certifications

As technology’s influence in every area expands, it generates massive volumes of data that can provide useful insights into the subject. In the last ten years, this has resulted in a boom in the data sector.  However, data collecting must be accompanied by data analysis to acquire decision-making insights. Data analytics assists firms and sectors in making sense of massive amounts of data to grow and flourish. Investing in data analytics solutions might mean the difference between a company’s success and failure in the now and future. This article will introduce you to the concept of data analytics and will provide you with all the essential details regarding data analytics courses by Masai.

Before we move to the discussion about data analytics courses by Masai, let us first understand the concept of data analytics.

What is Data Analytics?

Many individuals are unfamiliar with the term “data analytics.” It simply refers to all the processes and tools required to process a set of data and derive meaningful insights from it. Analytics is a wide phrase that encompasses the many tools and methods used for data analysis. Analytics business tools can be qualitative, such as medical quality of life surveys, or quantitative, such as statistical tools or software. They separate usable data from irrelevant data and analyze it to provide patterns and numerical data that can be used to make a profitable change.

Data analytics is an essential component of strategy development in all major organizations since it assists them in predicting customer trends and behaviors, increasing corporate productivity, and making evidence-based decisions.

Various Components of Data Analytics

You can use a variety of methods to process any set of data –

Data mining

It is the process of converting vast amounts of raw data into manageable bits of information. They also detect abnormalities in data sets and examine the relationships between data sets to find correlations between them. In many clinical trials, data mining is utilized to identify behavioral patterns in patient data.

Text analytics

Text Analytics is used to provide auto-correction for your phone and predictive typing for your emails. To construct algorithms, huge amounts of unstructured text must be processed. Linguistic analysis, pattern identification in textual data, and filtering out spam emails from relevant ones are all part of it.

Data Visualization

It is the process of presenting data in a visual format for easier evaluation. It aids in the comprehension of complex data. Bar charts, histograms, graphs, and pie charts are some examples.

Business Intelligence

This is the process of translating data into usable insights for a company. These findings are then utilized to develop commercial strategies such as product positioning and pricing. It entails the use of visual tools like heat maps, pivot tables, and mapping approaches.

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The Advantages of Data Analytics for Enterprises

Data analytics is a critical asset for businesses seeking a competitive advantage. Here are a few industries where data analytics can help.

Product Development:

Data analytics helps with prediction as well as knowledge discovery. It aids in comprehending the existing status of the business or process and serves as a solid foundation for forecasting future outcomes. Data analytics enables firms to comprehend the present market condition and adjust processes or trigger the need for new product development to meet market demands.

Targeted Content:

Knowing what clients want ahead of time makes marketing campaigns more personalized. It helps businesses to tailor their marketing to a certain portion of their customer base. It also assists them in determining which client category will respond best to the marketing. Furthermore, it saves money on the expense of persuading a customer to buy and improves the overall efficiency of marketing operations.

Data analytics can also help businesses uncover additional possible possibilities to improve processes or increase profitability. It aids in the identification of prospective problems, eliminating the need to wait for them to develop before acting on them. This enables businesses to evaluate which activities produced the best overall outcomes under varied conditions, as well as identify which operational areas are error-prone and which require improvement.

Advantages of a Career in Data Analytics

Before we give you all the information regarding data analytics courses by Masai, here are some of the advantages of pursuing a career in the profession – 

You can quickly learn the abilities needed for the job

Having a natural willingness to solve problems, regardless of your current career, will make it easier and more exciting for you to learn how to apply in-demand analytical tools and to specialize over time. 

The Occupation is in High Demand:

75% of Internet of Things (IoT) providers regard data analytics to be the most desired profession, while more than 68% of them are struggling to locate personnel with the necessary experience. Professional opportunities are expected to expand in the coming years.

Big Data Analytics provides cost-effective solutions and improves decision-making capacity in a variety of development areas, including healthcare, manufacturing, education, media, retail, and even real estate. You can select from a variety of industries based on your skills and preferences.

There are numerous high-paying positions available in the industry: The monetary benefits of pursuing a Data Analytics job may outweigh those of other IT professionals. Students and young people who are logically driven, computer knowledgeable, and outstanding communicators who want to make an above-average income while working fixed hours can choose a career in Big Data Analytics.

You Can Excel in the Industry if You Have a Knack for Math and Statistics:

A Big Data Analytics career move will help you to hone your skills in graph theory, real analysis, numerical analysis, applied statistics, and linear algebra.

It Gives You the Ability to Make Decisions:

Data analytics adds value to any organization by helping it to make educated decisions and gain a competitive advantage. With more firms relying on data professionals, you’ll collaborate with the organization’s key person to streamline decision-making layers from top to bottom and coordinate with local levels to act on insights.

Techniques for Data Analytics

Data analysts can process data and extract information using a variety of analytical methodologies and techniques. 

The Most Common Methods Used Are:

The process of assessing the relationship between dependent variables to discover how a change in one may affect the change in another is known as regression analysis.

Factor analysis requires reducing a huge data collection to a smaller data set. The purpose of this maneuver is to try to uncover hidden trends that would otherwise be difficult to spot.

Cohort analysis is the process of dividing a data collection into groups of similar data, which is frequently split down into consumer demographics. This enables data analysts and other data analytics users to delve deeper into the numbers about a certain subset of data.

Monte Carlo simulations simulate the likelihood of various events occurring. These simulations, which are frequently used for risk reduction and loss prevention, integrate many values and variables and often have stronger predicting skills than other data analytics methodologies.

Time series analysis follows data over time and establishes a link between the value of a data point and its recurrence. This data analysis technique is commonly used to identify cyclical tendencies or to forecast financial outcomes.

Now let us provide you with all the details about the data analytics courses by Masai.

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About Masai School

Prateek Shukla, Co-Founder, and CEO, of Masai School, was teaching with Teach for India during his pre-final year at IIT Kanpur when he discovered India’s education problem and how underutilized India’s genuine potential is. Several years later, while on holiday in Kenya and Tanzania, he met the Chieftain of the Maasai Mara Tribe. He learned about the tribe’s strong skilling strategies for staying capable and self-sufficient.

Back in India, he discovered that every technology company spends approximately 6 months training new personnel before allowing them to contribute to the organization’s goals. Prateek saw an opportunity to serve Bharat by bringing together Nrupul Dev and Yogesh Bhat to launch Masai School in June 2019. They set out to create a military-style coding institute based on the 9-9-6 intense training regimen, which runs six days a week from 9 a.m. to 9 p.m. The comprehensive program consists of 1200 hours of hands-on coding, 100 hours of soft skills training, 100 hours of mathematics, and other components.

Masai has risen at an astounding rate since then. With thousands of students enrolled, Masai School is leading the Outcome Driven Education Revolution in India, with additional courses like Data Analytics now available.

Masai’s headquarters are in Bengaluru, India. Their Web Development and Data Analytics courses are delivered live online in an interactive setting.

The institute offers courses in the fields of Web Development, Backend Development, and Data Analytics. Let us now see the details about data analytics courses by Masai.

Course Details for Data Analytics Courses by Masai

The course demands a commitment of 7 pm-12 am Monday-Friday and 3 pm-10 pm Saturday for a duration of 30 weeks in an intensive and immersive curriculum.

Modules

Module 1 

Microsoft Excel:

Microsoft Excel is the most versatile and sophisticated data analytics application. Learn how to deal with real-time data and how to use formatting strategies to display findings correctly and professionally. Data manipulation with Excel functions and features.

Advanced Excel Analytics:

Learn how to leverage lookup functions, advanced filtering, and sorting features to improve your interaction with data. Explore more sophisticated Excel features, including how to create dashboards with pivot features (Pivot tables, Pivot charts, Power Query), as well as how to use slicers to make dashboards more dynamic and user pleasant.

SQL (Structured Query Language):

SQL is used to share and manage data in relational database management systems (RDBMS), which store data in tables. Multiple files, each containing data tables, can also be linked together via a common field. Manipulate and organize data from several tables using SQL before tackling the required data form with other analytical tools.

Module 2

Programming Language Fundamentals:

Learn what a programming language is and how to construct programs that use variables, loops, conditions, and data structures.

Python as a Scripting Language:

Python as a programming language and data are introduced. Analytical tool for investigating various datatypes such as sets, tuples, lists, and dictionaries. Learn how to use several built-in functions as well as develop custom functions and conditional executions to build logic as needed. Investigate various debugging strategies, such as exception handling.

Experimental Data Analytics (EDA) with Python:

Explore numerous modules and packages while learning Exploratory Data Analytics with well-known Python libraries such as NumPy and pandas. Use other data visualization and model-building libraries, such as matplotlib.

Module 3

Guesstimates:

An Overview of Business Skills and Learn how estimation works in various business contexts. Solve a variety of real-world business challenges while learning how to organize your thoughts and approach to achieve better results and solve a certain class of business difficulties.

Extreme SQL:

Learn about joins and their broader categories, the concept of writing nested inquiries, partition by, analytical functions, and a few advanced query writing concepts, and lastly the best practices for writing SQL queries in advanced SQL.

Final Projects:

Collaborate on projects to collect, investigate, and analyze data to derive key insights that might aid in understanding real-world challenges and measuring the effectiveness of a given strategy.

Module 4

Tableau for Business Intelligence:

Tableau is a popular business intelligence tool in the analytics field. It is one of the best data visualization tools for analyzing data and gaining data-driven business insights. Learn how to extract meaning from massive datasets and how to construct dashboards in depth. Learn how to use Tableau to create storyboards that allow us to translate complex data into relevant insights.

Probability:

Learn about sample space, simple and compound events, set theory, union, intersection, Venn diagram, and mutually exclusive or disjoint events, as well as some numerical problems about them.

Statistics:

Introduction to descriptive statistics, including population vs. sample difference, statistical inference, frequency distributions, and cumulative distributions. Descriptive statistics will cover central tendency measurements such as mean, median, mode, and mode, as well as variation measures such as standard deviation, variance, Quartile and percentile, range, and InterQuartile range. Box plots, normal distribution plots, discrete and continuous random variables, pmf, cmf, pdf, CDF, hypothesis testing, chi-square test, and central limit theorem are examples of charts.

Examples of Case Studies:

Learn how to do research and analysis on various real-world business issues. Collaborate effectively to brainstorm and strategize alternative solutions to a difficult issue in its real-life setting. Learn about many best practices approaches and popular frameworks that might help us structure our approach.

Module 5

Introduction to Machine Learning:

Learn the difference between data and information, as well as the numerous use cases of Machine Learning such as prediction, picture identification, medical diagnosis, and financial and trading industries. Learn about the many types of Machine Learning models, which are classified as Supervised and Unsupervised, and further classified as Classification and Regression.

Machine Learning Models:

Various univariate and multivariate plots such as scatter plots, pair plots, box plots, uniform distribution plots, and so on.

Learning various machine learning algorithms such as linear regression, logistic regression, SVM, Decision tree, random forest, K-means clustering, and hierarchical clustering are two types of clustering algorithms.

Module 6

Projects on Predictive analytics:

Work on collaborative projects to build different Machine Learning models as per the business problem and explore all concepts that are important for understanding real-world applications.

Features That Make Data Analytics Courses by Masai the Most Sought After

• The institute has over 1400 hiring partners and is constantly expanding to bring you the best opportunities.
• The actual placement procedure begins when you have completed your course and passed the Masai Final Evaluation Test. The preparation for the placement procedure, on the other hand, begins during the final leg of your curriculum and lasts for a few weeks alongside the coursework.
• The Institute assists you in developing a portfolio, CV, and online profiles, and running you through many mock interviews. You will also be given prepared information for any opportunities or companies that come in for employment. As judged essential by the team, further one-on-one guidance is provided during the placement process.

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Eligibility Criteria for Data Analytics Courses by Masai

To Be Qualified for a Course, You Must Have the Following Qualifications:

• Courses are only available to Indian citizens.
• You must have a valid PAN card as well as an Aadhaar card.
• You must have a laptop and an active internet connection.
• Their Web Development Courses require a basic understanding of the English language.
• You must be available to start working immediately after finishing the course.

Age Criteria

18-28 years in data analytics

Academic Qualifications

• If you have completed the 12th grade through a CBSE/ICSE/State-recognized board of education or a diploma program.
• There is no prerequisite for training in coding.
• Dropouts from college may also apply.
• Part-Time Courses are accessible for 2022 graduates as well as working professionals (aged 18-28).

Entrance Exam

You have one opportunity to pass the Software Development test. If you do not pass the MSAT, you can apply to the next class.

Certification After Completing Data Analytics Courses by Masai

Upon graduation, the institute will provide a certificate of completion. However, Masai is not a degree-granting university, and they do not award bachelor’s or master’s degrees. Masai’s primary focus is on skill development and comprehensive learning. They have not partnered with any educational institution to provide certification. They believe that abilities are more important than degrees.

Let us go through some of the commonly asked questions regarding data analytics courses by Masai.

Frequently Asked Questions

Q1. Who is making use of Data Analytics?

Data analytics has been utilized by various industries, including travel and hospitality, where response times can be short. This industry can collect client data and determine where, if any, problems exist and how to resolve them. Healthcare is another industry that uses large amounts of structured and unstructured data, and data analytics can aid in making timely judgments. Similarly, the retail business makes extensive use of data to fulfill the ever-changing needs of customers. After pursuing data analytics courses by Masai, you also will be using data analytics for one of these sectors.

Q2. What are the different kinds of Data Analytics?

Before pursuing data analytics courses in Masai, you must know about the different types of data analytics. The four main types of data analytics are as follows. 

Descriptive analytics outlines what transpired over a specific time. Diagnostic analytics is primarily interested in the causes of events. Predictive analytics focuses on what is expected to happen soon. Finally, prescriptive analytics makes a recommendation.

Q3. What is the importance of Data Analytics?

Data analytics is important because it enables businesses to perform better. Companies that include it in their business models can assist cut expenses by identifying more efficient ways of doing business. Data analytics can also help a company make better business decisions and assess customer patterns and satisfaction, which can lead to new—and better—products and services. Because of the growing importance of data analytics, many institutes like Masai are offering courses in data analytics.

Conclusion

In a world that is more reliant on information and statistics, data analytics assists individuals and companies in ensuring the accuracy of their data. Using a variety of tools and approaches, a set of raw numbers can be transformed into informative, educative insights that guide decision-making and purposeful management.

After pursuing data analytics courses at Masai School, you can choose a profession in data analytics in any sector that does not confine you to a specific field. If you have the right set of technology skills, you can move and advance swiftly in the industries that most closely match your interests.

You can easily lay the groundwork by taking classes in the subject. Numerous prestigious colleges throughout the world provide diploma or degree programs in data analytics. You can choose a course based on your financial situation or convenience. This article has provided details about the data analytics courses by Masai.