Advanced Data Analytics

"Unlock insights, convey key discoveries, and implement data-driven decisions with Excel, R, SQL, and Statistical analysis."

Best Seller Expert 30 Participants   |   Durations : 04th May 2023 - 20th July 2023
Mentors Adarsha Shivananda   4.0


What are the Data Analyst course learning objectives?

  • Fundamentals of data analysis, including data cleaning, exploration, and visualization.
  • Hands-on experience with data analysis tools such as Excel, R, PowerBI, etc.
  • Data cleaning and organization using spreadsheets, SQL and R programming.
  • Presentation of data insights through dashboards, presentations, and visualization platforms like PowerBI and Tableau.
  • Application of statistical and machine learning methods for data analysis and insights extraction.
  • Effective communication of findings and insights to both technical and non-technical stakeholders.
  • Practical experience in solving real-world data analysis problems and working with large, complex datasets.
  • Awareness of the business context for data analytics and how data-driven insights inform decision making.
  • Enhance business performance by identifying growth opportunities, reducing costs, and improving overall performance through data insights extraction.

Course Content

1.1 Introduction, Home - Font, Alignment,Number,cells,Editing

1.2 Data - Sort, filter, Advanced filter, Data tools

1.3 Mathematical,character,date and logical functions

1.4 Lookup, Match and idex and conditional formatting

1.5 Pivot table and charts

1.6 Charts

1.7 Data visualizations

2.1 The various kinds of data types in python and its appropriate uses

2.2 Summarize data by using functions like: str(), class(), length(), nrow(), ncol()

2.3 Data Structures

2.4 Reading tabular data files

2.5 Reading from csv files

2.6 Installing packages

2.7 Pandas

2.8 Numpy

3.1 Sorting data

3.2 Merging dataframes

3.3 Data transformation

3.4 Strings and dates

3.5 Outlier detection

3.6 Handling NAs and Missing Values

3.7 Logical operations

3.8 Relational operators

3.9 Accessing Variables

3.10 Managing Subset of data

3.11 Character manipulation

3.12 Creating new variables

4.1 Understanding the Exploratory Data Analysis(EDA)

4.2 Implementation of EDA on various datasets

4.3 EDA packages

4.4 Aggregation

4.5 Computing basic statistics

5.1 Understanding on Data Visualization

5.2 Creating a bar chart, dot plot

5.3 Creating a scatter plot, pie chart

5.4 Creating a histogram and box plot

5.5 Other plotting functions

5.6 Plotting with base graphics

5.7 Plotting with Lattice graphics

5.8 Plotting and coloring

6.1 Computing basic statistics

6.2 Comparing means of two samples

6.3 Testing a correlation for significance

6.4 Hypothesis Testing

6.5 Classical tests (t,z,F), Chisquare


6.7 Summarizing Data

6.8 Data Munging Basics

6.9 Cross tabulation

7.1 Simple linear regression

7.2 Multiple Regression model

7.3 Logistic regression

7.4 Standardizing

8.1 Basics of SQL

8.2 Retrieving data

8.3 Data manipulation

8.4 Joins

8.5 Aggregation in SQL

9.1 Resume & LinkedIn Profile Building

9.2 Mock Interview Preparation

9.3 1 on 1 Career Mentoring Sessions

9.4 Placement Assistance

9.5 IFERP placement drive

About this Course

"Become a Data analyst with this Data analytics program. Study data cleansing, data visualization, statistical analysis, and an intro to machine learning. Utilize tools like Excel, R, PowerBI, and Tableau to work with data, using real-world datasets. After completing the course, you'll have the ability to detect patterns, trends, and make data-driven decisions. No prior coding or data analytics experience needed, suitable for all."

Why Data Analytics?

Data Analysts are still in high demand, as stated by the World Economic Forum. Companies recognize data analysis as an essential skill that provides valuable insights. The increase in data availability leads to a growing skill gap in data analytics, providing more job opportunities and career growth.

There are several factors that motivate individuals to pursue a career as a Data Analyst, including:

  • Rising demand for Data Analysts : The field of data analytics is rapidly expanding, and organizations are seeking professionals to make sense of the growing data.
  • Diverse career options : Data Analysts can work in a range of industries, such as finance, healthcare, marketing, and others. They can also progress into related roles, like Data Scientist, Business Analyst, or management positions.
  • High salary prospects : Data Analysts generally have high earning potential, and this trend is expected to continue as the demand for data analytics professionals rises.
  • Dynamic and ever-changing field : Data analysis is a constantly evolving field with new tools and methods emerging regularly, making it an exciting and dynamic career path.

Who should enroll for Data Analytics Courses?

Data Analytics course designed by IFERP ACADEMY is to help individuals who want to develop skills in data analysis and data-driven decision-making. Here are some examples of who could benefit from enrolling in a Data Analytics course:

  • Professionals looking to upskill : Data Analytics courses can be an excellent way for professionals in a variety of fields to upskill and develop new skills that are in demand in the job market. These may include professionals in business, finance, marketing, healthcare, and other fields.
  • Recent graduates : Recent graduates who are interested in pursuing a career in data analytics can benefit from a Data Analytics course to gain foundational skills and knowledge in data analysis, programming, and machine learning.
  • Career changers : Individuals who are interested in transitioning to a career in data analytics from another field can benefit from a Data Analytics course to develop new skills and gain a better understanding of the field.
  • Entrepreneurs and business owners : Entrepreneurs and business owners can benefit from a Data Analytics course to learn how to use data to make data-driven decisions, develop strategies, and gain insights into customer behavior.
  • Anyone interested in data analytics : Individuals who are simply interested in data analytics and want to learn more about data analysis, data visualization, and data-driven decision-making can also benefit from a Data Analytics course.

In summary, IFERP Data Analytics courses are designed for anyone who wants to develop skills in data analysis and data-driven decision-making, regardless of their background or career goals.

Case Studies :

Churn Prediction : is one of the most popular Big Data use cases in business. It consists of detecting customers who are likely to cancel a subscription to a service

HR Analytics : It mainly used to predict with which potential employee is going to leave the company

Customer Segmentation : It is the practice of dividing a customer base into groups of individuals that are similar in specific ways so companies can do marketing to each group effectively and appropriately

Campaign Measurement : Every business want to know the effectiveness of the campaign they ran and the lift in revenue because of the campaign

Recommendation Engines : Apply machine learning algorithms on broad set of data such as customer purchase data, contextual information ( device, time, third-party feedback ) to recommend products or services

Improve Customer Experience : (CX) by predicting user’s next actions and choices

Sentiment Analysis : Apply natural language processing to recognize sentiments of customer voice

Use Machine Learning to predict and alter marketers about expected business critical pivot moments ( such as churn, high valued customers, marketing leads )

Common job titles:

Data Analyst, Senior Data Analyst, Associate Data Analyst, Business Analyst, Junior Data Scientist, Finance Analyst, Operations Analyst, Marketing Analyst, Healthcare Analyst


Adarsha Shivananda
Data Science Manager | Author | Trainer | Content Developer | Speaker | Educator - AI, ML, NLP, Deep Learning, Analytics
30 Participants

Data Science Manager where he is working on building machine learning and AI capabilities for software products. His aim is to build a pool of exceptional data scientists within and outside of the organization to solve greater problems through brilliant training programs and always want to stay ahead of the curve. Previously he worked with Tredence Analytics and IQVIA. He worked extensively in the pharma, healthcare, retail, and marketing domains.

Authored 6 AI books, “Natural Language Processing Recipes” and "Natural Language Processing Projects" to name couple with Apress.

Mr Adarsha Shivananda is a regular speaker at top colleges in the area of AI to educate and encourage students to take up Data Science as their career option. He serves as a mentor for AI/ML course at great learning and other institutes.

AI Educator, AI/ML content developer, Data science trainer, Content creator, Analytics trainer, Corporate trainer, Freelance training, where he conduct online and classroom classes for aspiring Data Scientists. Also conducted workshops across India in this field. Data science consultant, Analytics consultant, AI consultant.


  • Collects, processes, and analyzes data to identify patterns, trends, and insights.
  • Cleans and transforms data to make it suitable for analysis.
  • Uses statistical methods and data visualization to analyze data and communicate findings.
  • Creates effective data visualizations and reports to communicate insights to stakeholders.
  • Identifies and solves business problems using data analysis.
  • Join IFERP academy advanced data analytics course with a Bachelor's degree in a relevant field, such as computer science, mathematics, statistics, or data science.
  • Develop key skills in data collection, cleaning, transformation, analysis, visualization, and report writing.
  • Gain practical experience referred by IFERP academy through internships, personal projects, or entry-level positions in data-related fields.
  • Build a portfolio of your work to showcase your skills and experience to potential employers.
  • Stay current with new tools and techniques in data analysis by attending conferences, taking courses, or participating in online communities.
  • Earning a certification from IFERP academy in data analysis would add value and that demonstrate your skills and knowledge to potential employers.

Although data analysts are well-paid worldwide and exponential demand for data analysts will never decline, data analysts' salaries vary in different sectors and nations. Data analysts' salaries depend on their skills, experience, company & location. IFERP academy’s Data Analyst course helps you achieve a higher salary, expertise, and skills to succeed in this lucrative growing profession. The average annual salary in top countries is:

India: Rs. 4,90,012
US (New York): $77,730
Canada: $64,962

  • Start with the fundamentals : Learn statistics, data structures, and data manipulation techniques.
  • Learn programming languages and tools : Use languages like SQL, R, or Python, and tools like Excel, Tableau, or Power BI.
  • Work on projects : Practice by working on real-world projects, either from case studies or live projects from IFERP academy.
  • Get certified : from IFERP academy to validate your skills.
  • Attend training programs : Attend online or in-person training programs to learn from experts.
  • Join online communities : Join forums, attend webinars, and participate in online communities to learn from experts and peers.
  • Keep learning : Stay updated with new tools and techniques in data analytics by reading blogs, attending conferences, or participating in online courses through IFERP academy.

There are several reasons why you might want to consider starting a career as a Data Analyst:

  • High Demand : Data Analytics is a growing field and there is a high demand for skilled professionals in this field across various industries.
  • Lucrative Salaries : Data Analysts earn competitive salaries, with potential for salary increases over time as they gain more experience and expertise in the field.
  • Varied Career Opportunities : There are many career paths within the field of Data Analytics, such as Business Intelligence Analyst, Marketing Analyst, Financial Analyst, and more.
  • Growth Opportunities : Data Analytics is a field that is constantly evolving, with new tools and techniques being developed all the time. This means there are many opportunities for professional growth and learning.
  • Impactful Work : As a Data Analyst, you will have the opportunity to make an impact on your organization's success by using data to inform strategic decisions.

Overall, a career in Data Analytics can be challenging, rewarding, and fulfilling for those with an interest in data, technology, and problem-solving.