Diploma in Data Analytics Course Details
The Data Analytics course is a meticulously designed program that provides a deep dive into the world of data analytics. It covers essential areas such as Statistical Analysis, Python for data manipulation and analysis, Machine Learning for predictive modeling, SQL for database querying, Tableau for data visualization, and Git and GitHub for version control. Additionally, it introduces you to Big Data technologies like Hadoop and Spark. This course offers a balanced mix of theoretical knowledge and practical skills, preparing you to excel in the ever-evolving field of data analytics. It caters to both beginners seeking foundational knowledge and professionals aiming to enhance their skills, offering a learning path that is customised to fit your needs.
What you will Learn
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Module 1: Microsoft Excel:
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In this module, participants will explore fundamental
concepts of data analysis, centering on Microsoft Excel. The
journey begins with an introduction to data and its analysis
process, covering the basics of Excel, including working
with templates. The progression includes exploring data,
studying Excel functions, and understanding various function
types, such as Common, String, Logical, Numerical, and Date
& Time functions. Participants will develop proficiency in
Vlookup and Hlookup, conditional selection, and logical
operators. The module extends its coverage to encompass
critical Excel features like Power Query for efficient data
importing and transformation, Power Pivot for advanced data
modelling, and macros in Visual Basic for Application (VBA)
for automation. Additionally, participants will learn about
data validation, what-if analysis, and solving linear
optimization problems using Excel Solver. This segment aims
to advance participants' skills in Microsoft Excel,
providing a comprehensive understanding of data analysis
tools and techniques.
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Module 2: Microsoft PowerBI
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Over the course of this advanced program, participants will
embark on a comprehensive journey into Microsoft Power BI
Desktop. The syllabus unfolds, covering crucial aspects of
data analysis. Topics include data connection strategies,
Power Query Editing, and the utilization of M functions for
effective data manipulation. Participants will learn to
leverage grouping and binnings, explore aggregation
techniques, and master merging and appending queries. The
program delves into essential concepts such as data
modelling, table relationships, and various filtering
methods. As the days progress, participants gain proficiency
in advanced topics like Drill Down and Drill Through
Filters, Data Analysis Expression (DAX) functions, and the
creation of charts and visuals for effective data
representation. The program culminates with a focus on
creating interactive dashboards, preparing summary reports,
and exploring specialized visualizations like Power BI Q&A,
Key Influencer visuals, and Time Series Analysis.
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Module 3: SQL for Data Analytics
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In this extensive SQL program, participants undergo a
comprehensive exploration of database management and SQL.
The curriculum begins with an introduction to data in the
21st century and the installation of essential SQL software.
Participants progress through foundational topics, including
the purpose and significance of databases, basic SQL
queries, and functions like SELECT, AS, and CONCAT. Advanced
concepts cover filtering data, logical operators, IS
Keyword, BETWEEN + AND, IN, LIKE, and DATE Functions. The
program explores JOIN operations, GROUP BY, HAVING, ORDER
BY, GROUPING SETS, UNION, UNION ALL, ROLL UP, and WINDOW
functions. Further exploration encompasses conditional
statements, NULLIF, VIEWS, subqueries, stored procedures,
and WITH CTE. Practical aspects of database creation, data
types, Boolean type, storage methods, and manipulation
operations like INSERT, UPDATE, DELETE, DROP, and ALTER are
covered. The program concludes with discussions on database
design methodologies, ER models, primary and foreign keys,
and relationship determination. Throughout this program,
participants acquire comprehensive skills in SQL, empowering
them to proficiently design and manage databases.
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Module 4: Tableau for Data Analytics
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In this extensive Tableau program, participants embark on a
comprehensive journey into the realm of data visualization.
The curriculum covers fundamental concepts such as
connecting to data sources, creating visualizations, and
cleaning and shaping data. As participants progress, they
delve into advanced techniques, including the creation of
calculated fields, blending data from diverse sources, and
crafting a variety of charts, from basic to advanced types.
The program explores the nuances of building groups,
hierarchies, and specialized visualizations like maps and
geospatial analyses. Focusing on dashboards, stories, and
the publishing process, the program concludes by addressing
collaborative features, security considerations, and
permissions within Tableau. This holistic approach equips
participants with a robust skill set for leveraging Tableau
effectively in data visualization and analysis.
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Module 5: Data Analytics with Python
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In this module, participants will gain a solid foundation in
Python programming for data analytics. Beginning with an
introduction to Python and its marketplace, the curriculum
covers Anaconda environment setup and practical exercises
using Jupyter Notebook. Participants will progress through
fundamental Python concepts such as syntax, variables, data
types, operators, and conditional statements. The module
extends to more advanced topics like loops, inbuilt and
user-defined functions, object-oriented programming, file
handling, error handling, and working with modules and
libraries. Practical application includes creating GUI
applications with Tkinter.
Skills and Tools you will learn
- Excel
- Power BI
- SQL
- Python
- Tableau
