Data Analysis and Visualization Training

These days, Data Analysis and visualisation are in high demand, both nationally and internationally. So, IT Training Nepal has launched the training programme that trains a novice candidate into a skilled professional. We have been conducting Data Analysis and visualisation training classes by market experts who enable learners to become self-sustaining experts.

Data Analysis and Visualisation with IT Training Nepal

No matter what and how many resources you have invested, unless there is timely and proper information, you cannot survive and flourish in today’s highly competitive world. So, IT Training Nepal prioritises producing professionals who can help any organisation in improving marketing strategies, consumer relations, and management strategies by implementing various tools they learn here. Along with skills and knowledge required for building a career, training at ITN also develops students to look deeply into data to create a competitive edge over rivals.

During their 75-day stay with us, our expert trainers intend to instill candidates with essential analytical and visualisation skills required for their professional development.

Benefits of Data Analysis and Visualisation Training

Only those organisations survive and flourish that have timely and proper information, as it allows them to make the right decisions. So, individuals who have the right skills and tools are in a position to help such organisations. Some of the benefits of Data Analysis and Visualisation training are:

  • It helps identify the primary factors that hold the key to generating the information.
  • For business people and entrepreneurs, it helps in identifying products or services that need to be improved.
  • Such skills make data more memorable for stakeholders as they present the concept.
  • Data visualisation helps organisations understand what kind of modification is needed to satisfy the market needs.
  • They can predict forthcoming events and help prepare to mitigate any negative effects.

How is the “Data Analysis and Visualisation” training course designed and implemented?

The training course intends to encompass the whole process of data analysis from its collection, cleaning, analysis, visualisation, and telling result-based stories. The training at IT Training Nepal is carried out in two phases, namely:

  • Basic: During this stage, candidates learn all the fundamentals of data collecting and cleaning skills. Trainees during this stage also learn the basics of data manipulation in Excel, including Basic calculations, working with text, conditional formatting, special functions, and organising data.
  • Advanced:  The training moves to the advanced section with SQL, acquiring essential SQL skills to query databases, retrieve relevant information sets, and perform information manipulation tasks. Here, candidates develop skills in combining tables using JOINs: INNER, LEFT, RIGHT, and FULL.

The training moves to Python, where students learn the basics and how to run Python. With skills in Python libraries and manipulating data through Aggregations, Filtering, Merging, and GroupBy, the trainee develops skills in Matplotlib, Seaborn, and finally makes different types of charts.

During Data Extraction and Preprocessing, trainees can address fixing data issues, changing data, And Cleaning data within BI. The Power BI and Tableau allow our participants to learn to create compelling visualisations and interactive dashboards using Tableau.

How is Data Analysis and Visualisation Training Conducted?

The training duration is about 2.5 months, and the duration of the class is about 1.5 hours. Each class has 6-8 students, so our trainees have enough time to guide each student. Revision classes are also available whenever demanded. Based on students' learning ability and educational backgrounds, groups are also formed for ease. Home assignments and tests, along with feedback, are a regular feature of the training programme.

The training is considered complete once students complete a capstone project using all the tools learned during the training to learn real-world experience.

So, enquire about the course outline, details on the fee structure, and timetable by calling IT Training Nepal, or you may also visit personally.

Targeted audience

Data Analysis and Visualisation Training course at IT Training Nepal is designed for professionals who aspire to build a career in the field of data analytics. As the course covers the fundamentals before diving into advanced topics, one should be surprised to see our trainees working as:

  • Aspiring Data Analysts and Scientists: Anyone looking to build a strong foundation for a career in the data field.
  • Business Professionals: Managers, marketers, and analysts who need to leverage data to make informed decisions and present findings to stakeholders.
  • Students and Researchers: Individuals who want to organise and visualise data for academic projects and publications.
  • Anyone Looking to Upskill: Professionals from any industry who want to improve their data literacy and analytical skills to stay competitive in the job market.
  • Business entrepreneurs: With the knowledge and skills they learn, trainees may evaluate the market and establish a business organisation of their own.
  • Market Analyst: The trainee develops deep knowledge and understanding of the market, which allows them to make a rightful prediction. This skill helps business organisations to understand consumers' demands and launch the product as demanded.
  • Planners and policy makers: With the knowledge and skills that trainees learn, they are qualified enough to work as planners and policy makers, allocating proper resources for growth.
  • Stock traders: Our trainees are qualified to draw a meaningful conclusion by analysing the data they hold. By analysing the present trend, they can evaluate the market correctly, allowing them to work as stock traders.

Key Highlights of the Course

Carefully structured and overseen by experienced instructors with deep market insight, we are committed to producing skilled individuals. We have a good market relationship, so our curriculum is designed in collaboration with industry experts, ensuring that candidates gain the skills and knowledge required for a meaningful career. We also encourage our candidates to hone their skills by participating in Real-World Projects. With our good market relationship, exceptional candidates also earn job placement in various recognised industries.

Some of the key features of our curriculum are:

  • Holistic Curriculum: The course covers the entire data analysis lifecycle, from foundational data handling in Excel to advanced visualization with Power BI and Tableau.
  • Practical, Hands-on Experience: You will work on 20+ real-world projects across various industries like finance, e-commerce, healthcare, and social media. These projects will give you practical experience with data manipulation, analysis, and visualisation.
  • Mastering Key Tools: The syllabus provides in-depth training on industry-standard tools, including ExcelMySQLPython (Pandas, Matplotlib, Seaborn)Power BI, and Tableau.
  • End-to-End Projects: The capstone projects challenge you to work on a complete data project from beginning to end, simulating a real-world professional scenario.
  • Diverse Application: You'll gain experience in a wide range of applications, including creating sales dashboards, analysing customer behaviour, and even building a movie recommendation system.

Skills the candidates learn

We have a well-equipped classroom and a fully functional laboratory where students are trained by market-skilled professionals. Our instructor focuses on each individual to bring out the best in them. We also encourage our trainees to participate in classroom discussions, the capstone project, and report presentations, honing their skills.

Some of the important skills that trainees learn at IT Training Nepal are:

  • Master SQL and Databases: Learn querying, joins, CTEs, and window functions with MySQL, PostgreSQL, and SQL Server.
  • Develop ETL and Data Engineering Skills: Build ETL pipelines and work with cloud data warehouses like BigQuery, Snowflake, and AWS Redshift.
  • Create Advanced BI Dashboards: Design and automate interactive reports using Power BI and Tableau.
  • Gain Expertise in Statistical Analysis and ML: Apply probability, hypothesis testing, and predictive modelling with Python (Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow).
  • Work on Real-World Projects: Gain hands-on experience in data analytics and visualisation through practical applications.
  • Automate Reporting and Data Processing: Implement efficient workflows for business intelligence and decision-making.
  • Apply Machine Learning and NLP: Utilise ML techniques for predictive analytics and natural language processing.
  • Develop Full-Stack Data Analysis Projects: Build end-to-end data solutions integrating querying, BI reporting, and ML insights.

Career opportunities for trained individuals
Learning Data Analysis and Visualisation training opens the door to many exciting careers. The graduates are properly seated to win a career in a big and stable company or a promising startup, companies across Nepal. The knowledge gained in this training enables you to mine large databases and transform the information retrieved into effective solutions. 
Data Analysis and Visualisation training graduates will be well-positioned to pursue a wide range of exciting careers, including:

  • Data Analyst
  • Data Scientist
  • Business Analyst
  • Data Engineer
  • Business Intelligence Analyst

 With the rapid growth of the data science and analytics field in Nepal, this training program provides you with the necessary skills and knowledge to embark on a rewarding and fulfilling career

Syllabus Expand All
  • What Data Analytics is about
  • Different kinds of analytics: Descriptive (what happened), Diagnostic (why it happened), Predictive (what will happen), and Prescriptive (what should be done)
  • Key steps with data: Collecting it, cleaning it, exploring it, visualising it (making charts), and using statistics
  • Basic calculations: SUM, MIN, MAX, AVERAGE, COUNT
  • Working with text: CONCAT (joining text), TRIM (removing spaces), UPPER (uppercase), LOWER (lowercase), PROPER (first letter capital), SUBSTITUTE, REPLACE
  • Conditional Formatting (changing cell appearance based on rules)
  • Special functions: IF (logical tests), DATEDIF (date differences)
  • Organising data: Sorting, Filtering, using Tables, and Data Validation (controlling what data can be entered)
  • SQL basics for asking databases questions: SELECT (choose data), WHERE (filter data), GROUP BY (group results), ORDER BY (sort results), HAVING (filter grouped results)
  • Combining data from different tables using JOINs: INNER, LEFT, RIGHT, FULL
  • More complex SQL: Subqueries (queries inside other queries), Window Functions
  • Examples of using SQL for real-world problems
  • Hands-on practice: Getting data from databases and saving it to Excel or Python
  • Python basics: Its syntax (how to write code), variables (for storing data), data types (like numbers or text), loops (repeating actions), and functions (reusable blocks of code)
  • Using Jupyter Notebooks for writing and running Python code
  • Working with Pandas (a tool for data): Series (single columns), DataFrames (tables of data), Indexing (finding data by label)
  • Reading data from CSV files, Excel files, and simple access to APIs (Application Programming Interfaces)
  • Changing and combining data: Aggregations (summarising), Filtering (selecting data), Merging (combining DataFrames), GroupBy (grouping data)
  • Visualising data with Python:
    ○ Basics of Matplotlib for creating plots
    ○ Introduction to Seaborn for more attractive statistical plots
    ○ Making different types of charts: Line charts, Bar charts, Heatmaps, Histograms
  • Where data comes from: Databases, CSV files, Excel files, and read-only APIs
  • Fixing common data issues: Dealing with missing values, duplicate entries, and outliers (unusual data points)
  • Changing data: Data type conversion (e.g., text to number), normalisation (scaling data), transformations
  • Using Power Query (with its M language) to clean data specifically within Power BI
  • Practical work: Cleaning example data (like sales or customer information) using Excel, Python, and Power BI
  • Measuring the centre of data: Mean (average), Median (middle value), Mode (most frequent value)
  • Measuring how spread out data is: Range (difference between max and min), Variance, Standard Deviation
  • Understanding the shape of data distributions: Skewness (how asymmetrical it is), Kurtosis (how peaked or flat it is)
    Correlation Analysis: Finding relationships between different data points
  • Creating visualisations to show how data is distributed
  • Hands-on practice: Exploring a real dataset (e.g., sales or HR data)
  • Basics of Power BI and Tableau: Understanding their layout and features
  • Connecting these tools to data from Excel, CSV files, or SQL databases
  • Cleaning data using Power Query directly within these tools
  • Data Modelling: Setting up connections between different data tables (relationships), and using a Star Schema (a common way to organise data for analysis)
  • Building data models that are ready for creating dashboards
  • Using DAX (Data Analysis Expressions) for calculations and creating visualisations
  • Key DAX functions: SUMX, CALCULATE, and Time Intelligence functions (for analysing data over time)
  • Creating interactive visual elements: Slicers (for filtering data), Drill-downs (exploring data in detail), Cards (showing single key numbers), and KPI Visuals (Key Performance Indicators)
FAQs

Both Data Analysis and Visualization are part of the data storytelling. Data Analysis usually find the insights while Data Visualization present those insights visually for better understanding.

Data Analytics is the process of monitoring raw data to discover meaning of the data while Data Visualization makes that meaning accessible through visuals.

Python, SQL, R Programming, Julia, Excel, PowerBI, Spark, etc are tools mostly used for Data Analysis.

Yes certifications can be useful in data analysis and visualization especially for building foundational skills, learning industry tools and boosting your credibility. However employers value practical skills and hands-on experience more than certification alone so you must build a portfolio with real-world projects, internships and problem solving techniques.

SQL(Structured Query Language) is a tool used in data analysis for querying and manipulating the relational databases. It is mostly important for data cleaning, data aggregation, data retrieving and getting direct access to data.

Banking & Finance, Education, Healthcare, Manufacturing, IT & Telecommunications, Retail & E-commerce hires data analysis and visualization the most.

Some of the common challenges in data analysis and visualization includes Poor Data Quality, Tool Limitations, Security & Privacy Concerns, Misinterpretations of Results, etc.

The salary for data analysts and visualization experts differs in skills, experience and location. In Nepal, entry level experts may earn around NPR 3 lakhs per year, mid-level experts typically earn around NPR 4-5 lakhs per year and senior experts may earn around NPR 7-10 lakhs per year.
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