Data Analysis Associate
| S. No. | NOS / Module Name | Topics | Theory (Hours) | Lab (Hours) | Learning Outcomes |
|---|---|---|---|---|---|
| 1 | Perform basic calculation using spreadsheet | Introduction to data analytics and data science, Windows and Spreadsheet | 10 | 20 |
• Understand features of Spreadsheet • Create & save worksheet/workbook • Understand layouts, text formats, alignment • Use basic functions, formulas, sorting • Understand graphs in Excel |
| 2 | Manage structured data | Database concepts | 30 | 30 |
• Introduction to databases, advantages of DBMS • Keys: candidate, primary, alternate, foreign • Entity & referential integrity • ER model and SQL • Data mining, warehouse, cleaning & aggregation |
| 3 | Analyze data using spreadsheet tool | Fundamentals of statistics, Pivot Table, What-if Analysis | 30 | 30 |
• Conditional formatting, charts & advanced charting • Pivot Table, data validation, filtering • What-if analysis • Probability, regression analysis, descriptive statistics |
| 4 | Manage data in Open Source tool | Linux basics, Ubuntu installation, Commands & Permissions | 10 | 20 |
• Setup virtual machine & Ubuntu • File system, mounting, searches • Text editors, commands, piping & filtering • Users, groups, permissions & security |
| 5 | Visualize data graphically | Tableau | 20 | 40 |
• Introduction to Tableau • Connecting to Excel, CSV, Databases • Formatting, sorting & creating charts |
| 6 | Installation of Hadoop & Java Programming | Hadoop framework & Core Java | 30 | 30 |
• Install Hadoop & environment setup • Java OOPs, loops, methods, arrays • HDFS concepts & commands • Hadoop cluster setup & architecture |
| 7 | Manage big data using Hadoop | Big Data analytics using MapReduce & Hive | 10 | 20 |
• Big Data concepts & importance • MapReduce implementation • Hive concepts & case studies |
| 8 | Implementation of use cases | Use cases in Data Analytics | 10 | 20 | • Implement practical use cases of Data Analytics |
| 9 | Employability Skills | Soft skills & communication | 60 | • Job readiness skills beyond technical knowledge | |
| 10 | OJT / Project | On-the-job training | 30 | • Hands-on exposure to workplace environment | |
| Total Duration | 450 | — | |||
| S. No. | NOS / Module Name | Topics | Theory (Hours) | Lab (Hours) | Learning Outcomes |
|---|---|---|---|---|---|
| 1 | Perform basic calculation using spreadsheet | Introduction to data analytics and data science, Windows and Spreadsheet | 15 | 15 |
• Understand features of Spreadsheet • Create & save worksheet/workbook • Understand layouts, text formats, alignment • Use basic functions, formulas, sorting • Understand graphs in Excel |
| 2 | Manage structured data | Database concepts | 15 | 15 |
• Introduction to databases, advantages of DBMS • Keys: candidate, primary, alternate, foreign • Entity & referential integrity • ER model, SQL basics • Data mining, warehouse, cleaning & aggregation |
| 3 | Analyze data using spreadsheet tool | Fundamentals of statistics, Pivot Table, What-if Analysis | 30 | 60 |
• Conditional formatting, charts & advanced charting • Pivot Table, data validation, filtering • What-if analysis • Probability, regression analysis, descriptive statistics |
| 4 | Manage data in Open Source tool | Linux basics, Ubuntu installation, Commands & Permissions | 15 | 15 |
• Setup virtual machine & Ubuntu • File system, mounting, searches • Text editors, commands, piping & filtering • Users, groups, permissions & security |
| 5 | Visualize data graphically | Tableau | 20 | 40 |
• Introduction to Tableau • Connecting to Excel, CSV, Databases • Formatting, sorting & creating charts |
| 6 | Installation of Hadoop & Java Programming | Hadoop framework & Core Java | 15 | 15 |
• Install Hadoop & environment setup • Java OOPs, loops, methods, arrays • HDFS concepts & commands • Hadoop cluster setup & architecture |
| 7 | Manage big data using Hadoop | Big Data analytics using MapReduce & Hive | 30 | 30 |
• Big Data concepts & importance • MapReduce implementation • Hive concepts & case studies |
| 8 | Front end application development | Java with Hive | 20 | 40 |
• Advanced Java, Applets, Swings • JDBC connectivity, ODBC bridge • Database connectivity with Applets |
| 9 | Implementation of use cases | Use cases in Data Analytics | 20 | 40 | • Implement practical use cases of Data Analytics |
| 10 | Employability Skills | Soft skills & communication | 60 | • Job readiness skills beyond technical knowledge | |
| 11 | OJT / Project | On-the-job training | 30 | • Hands-on exposure to workplace environment | |
| Total Duration | 540 | — | |||
Data Analysis Associate
- We all know that data is always the backbone of any business, and organizations are constantly looking for skilled professionals who can collect, process and analyze data to make smart decisions. If you want to start your career as Data analyst then this is the right time for this. It is the most demanded field these days, and our data analyst course in Chandigarh is the perfect choice to start your career. This is a 12 month, 450 hour program which is designed to give students a very strong foundation in data analysis, statistical methods, database management, programming and visualization tools. The curriculum includes both the practical and the theoretical so that you can learn not just the concepts but also how to apply them in real-world projects. By the end of the course, you will be job-ready and capable of turning data into valuable insights for any kind of organization.
Overview of the program
- Our course duration is about 12 months or 450 hours; the mode of the program is classroom training, hands-on labs, etc. The course is structured to provide a complete journey in data analytics, starting from the basics of computer skills and excel, and progressing to advanced topics like Python/R programming and business intelligence tools like as power BI and Tableau. You can learn the skills in terms of a project to showcase your ability in a real-world scenario.
The Course Modules
- These modules will help
- 1. Fundamentals of Computer and Excel (90 Hours | NSQF Level 4)
- 2. Introduction to Data Analysis and Statistics (100 Hours | NSQF Level 4)
- 3. Database Management using SQL (60 Hours | NSQF Level 4)
- 4. Data Analysis using Python/R (90 Hours | NSQF Level 4)
- 5. Data Visualization using Power BI/Tableau (50 Hours | NSQF Level 4)
- 6. Employability Skills (40 Hours | NSQF Level 4)
- 7. Capstone Project (20 Hours | NSQF Level 4)
What Is the Eligibility Criteria?
- The criteria for eligibility is very simple
- -Student who is pursuing or has completed B.Tech/ BCA/ BSC in Computer science, IT or a related field of study.
- - Diploma Holders after 10th and 12th with technical background
- - Graduates from commerce statistics or mathematics looking to upskill.
- - Working professionals wanting to shift into data analytics
Why Choose Our Hartron Advance Skill Centre?
- Data is being called the new oil when it is about the strategy, analyzation of customer data, etc. And companies of every size are investing heavily in analytics. From e-commerce to healthcare or banking, the businesses need professionals who can interpret data and drive decisions of business. The world is a hub for education and IT companies, offering an excellent opportunity for students to learn and build a successful career in this field. If you want to increase your career growth, then this is the best time to start with this. If you are looking for a data analyst course in Chandigarh, then we are the one-stop solution for you.
- This is the right time to enroll today. if you are passionate about the numbers, problem-solving and technology, this course is for you and will open the doors to a rewarding opportunity. For more information, just call us, our team of experts, and get the detailed overview of the course and consult today.