Data Analytics Course Syllabus 2024: Fees, Duration, Eligibility, Details

Data Analytics: An Overview

Data Analytics Course Syllabus 2024: Fees, Duration, Eligibility, Details, In today’s data-driven environment, businesses and organizations rely heavily on data analysis to make strategic choices crucial to their development and survival. With data analysis, organizations can make well-informed and thoughtful decisions. Due to the high demand for skilled data analysts, there are many courses available that cover the comprehensive material included in a data analyst course syllabus.

What is Data Analytics?

Data analytics is a multidisciplinary field that uses techniques from math, statistics, and computer science to extract insights from data sets. It involves everything from analyzing data to developing methods for data collection and designing frameworks for data storage.

Data Analyst Course Syllabus

The data analyst course syllabus offers comprehensive training in data extraction, analysis, and manipulation using various software and specialized systems. The curriculum covers essential topics such as Mathematics and Statistics, Data Structures, Simulation, Data Collection, and Data Comparison.

While the exact syllabus can vary between different programs, common topics in data analytics courses typically include:

Data Structures and Algorithms	Pricing Analytics
Supply Chain Analytics	Data Collection
Probability and Statistics	Marketing Analytics
Customer Analytics	Data Visualization
Relational Database Management Systems	Optimization
Retail Analytics	Statistical Analysis
Business Fundamentals	Machine Learning
Social Network Analytics	Forecasting Analytics
Text Analytics	Simulation

Data Analytics Engineering Syllabus

The curriculum for the engineering Big Data Analytics program encompasses the following topics:

Engineering Mathematics	Principles of Programming	Data Structures
Operating Systems	Computer System Architecture	Python Programming
Object Oriented Programming	Design and Analysis of Algorithm	Software Engineering & Project management
Big Data Ingestion	Design Thinking	Formal Languages and Automata Theory
Probability & Statistics for Engineers	Advanced Database Management Systems	Data Communication and Computer Networks
Computer Graphics	Big Data Storage	Disk Based Processing
Modelling and Simulation	Human Computer Interface	Compiler Design
In Memory Processing	Advanced Functional Thinking	Cryptography and Network Security
Image Processing & Pattern Analysis	Stream Processing	Big Data Search
Software Reliability & Testing	Software Quality Assurance	Data Exploration at Scale

Data Analytics Skills

To excel in data analytics, candidates must have strong numerical and analytical skills and a good understanding of computer software such as Python, SQL, R, Machine Learning, and Microsoft Excel. Key areas include:

1. Python

File Operations using Python	Loops
Syntax	Python Lists
Functions, Function Arguments, and Control Flow	Modules
Decorators and Generators	Dictionaries
Errors and Exception handling	Comparisons and Operators

2. Microsoft Excel

Create Workbooks	Data Formatting
Formulas Usage	Slicers
Create Pivot Tables	Graphs
Cell Referencing	Functions and Formulas
Charts Edit	VBA

3. R Programming

Background and Nuts & Bolts	Loop Functions and Debugging
Programming	Simulation & Profiling

4. SQL

Basic Concepts	Database Creation
Entity-relationship Modeling	Adding records to Table
Relational Model	SQL Subqueries
Data Manipulation	SQL Injections

5. Machine Learning

Introduction to Learning Methods: Supervised, Unsupervised, and Reinforcement Learning	Data Preprocessing and Data Mining
Decision Tree	Database & SQL
Linear Regression	Exploratory Data Analysis
SNM	Logistic Regression
CNN	Naive Bayes

Books	Authors
The Elements of Data Mining, Statistical Learning, Inference, and Prediction	Robert Tibshirani, Trevor Hastie, Jerome Friedman
Data Analysis Software: Programming with R (Statistics and Computing)	Robert Tibshirani, Trevor Hastie, Jerome Friedman
Probability & Statistics for Engineers & Scientists	Ronald E. Walpole, Sharon L. Myers, Raymond H. Myers, and Keying Ye
Data Mining and Analysis	Mohammed J. Zaki, Wagner Meira

Data Analytics Books

Data Analytics Tools

Various tools are available in the market to meet the growing demand for data analytics. Some top tools include:

Tool	Details	Organizations Using
R and Python	R and Python, the programming languages are used in the Data Analytics field. R tool is used for Statistics and Analytics, whereas Python is a high-level interpreted language.	ANZ, Google, Firefox, YouTube, Netflix, Facebook
Microsoft Excel	Microsoft Excel provides users with features like sharing workbooks, working in real-time collaboration, adding data to Excel directly from a photo, and many more features.	McDonald’s, IKEA, and Marriott
Tableau	Tableau allows you to work on a live data set and spend less time on Data Wrangling. It is a free tool.	Citibank, Deloitte, Skype, Audi
RapidMiner	RapidMiner, a tool for data processing and building Machine Learning models. Studio, GO, Server, Real-Time Scoring, and Radoop are the products of RapidMiner.	BMW, Hewlett Packard Enterprise, EZCater, Sanofi
KNIME	Konstanz Information Miner (KNIME) is free and open-source for data analytics, reporting, and integration. KNIME provides two software: the KNIME Analytics Platform and the KNIME Server.	Siemens, Novartis, Deutsche Telekom, Continental
Apache Spark	Apache Spark provides an open-source community and an interface for programming that identifies any fault tolerance and implicit data parallelism. The current version of Apache Spark is version 2.4.5.	Oracle, Hortonworks, Verizon, Visa
Power Bl	Power BI is a Microsoft-based product used in business analytics.  Power BI Embedded, Power BI Premium, Power BI Desktop, Power BI Mobile, Power BI Pro, and Power BI Report Server are the products of Power BI.	Adobe, Heathrow, Worldsmart, GE Healthcare
QlikView	QlikView is a Business Intelligence, Data Visualization, and Data Analytics tool that helps accelerate business value. Various tools and services are available for free or a free trial of 30 days.	CISCO, NHS, KitchenAid, and Samsung
Talend	Talend is a tool that efficiently manages all the steps involved in the ETL process and delivers accessible and clean data for users. Stitch Data Loader, Talend Pipeline Designer, Talend Open Source, Talend Cloud Data Integration, and Talend Data Fabric are free or available for 14 days.	ALDO, ABInBev, EuroNext, AstraZeneca
Splunk	Splunk is a tool to analyze the data gathered from applications and websites. Splunk Free, Splunk Enterprise, and Splunk Cloud are the features of Splunk that can be accessed for free for a limited period.	Dominos, Otto Group, Intel, Lenovo

Entrance Exams for Data Analytics

Some entrance exams for pursuing data analytics courses include:

• JEE MAINS & JEE Advanced
• CUET
• CAT
• MAT
• GATE
• JNUEE
• NIMSEE

Distance Education in Data Analytics

Online distance programs for data analytics usually last 12 months and are recognized for employment in both private and state sectors. These programs are ideal for those who cannot afford full-time courses or do not meet eligibility requirements.

Data Analytics Course Eligibility

Eligibility varies by course type:

• Diploma/Postgraduate Diploma: Graduation in Science or Engineering with Maths/Statistics/CS/IT as a core subject.
• Undergraduate Courses: Class 10 & 12 pass with knowledge of Statistics, Mathematics, and Programming.
• Postgraduate Courses: Graduation in Science or Engineering with advanced knowledge of Statistics, Mathematics, and Programming.

Apart from this, given below professionals are also eligible to pursue courses in Data Analytics:

• Non-IT Professionals
• BI Professionals
• Data Analytics Professionals
• Project Managers
• Software Developers
• Information Architects

Data Analytics Course Fees

The fees vary depending on the course type:

• Certification Course: ₹5000 – 10,000
• Diploma Course: ₹9,300 – 2,00,000
• Undergraduate Course: ₹90,000 – 21,00,000
• Postgraduate Course: ₹20,000 – 23,00,000

Also, the Data Analysis course fee depends on the course duration, the distinctive features each institute provides, and the post-course assistance. Online and offline institutes provide high-grade coaching, so sometimes, the syllabus isn’t the determinant of the difference in data analytics course fees for various institutes. Practical projects and access to learning portals, study materials, etc., can be significant factors for the difference in data analytics course fees.

Career Scope in Data Analytics

Data analytics offers high-paying jobs in sectors like banking, education, government, healthcare, marketing, e-commerce, and research. Job roles include:

• Data Analyst
• Big Data Visualizer
• Big Data Engineer
• Data Strategist

Job Roles in Data Analytics

Data Analyst	Big Data Visualizer	Big Data Engineer
Data Strategist	Big Data Specialist	System Administrators
Network Managers	Database Administrator	Big Data Architect

Top Recruiters in Data Analytics

Major recruiters include Amazon, Google, Flipkart, Facebook, Reliance, Accenture, TCS, Wipro, Citrix, IBM, LinkedIn, Deloitte, Ernst & Young, L&T, and HCL.

Benefits of Data Analytics Courses

• Learn essential data analysis tools and techniques.
• Develop critical thinking and problem-solving skills.
• Gain industry-relevant knowledge.

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Conclusion

The data analytics course syllabus encompasses a broad range of skills and modules, preparing individuals to make impactful business decisions through data-driven insights. The comprehensive syllabus empowers individuals to shape the world with data.