International Certification Program In Data Science And Business Analytics at Institute of Product Leadership, Bangalore

By Institute of Product Leadership, Bangalore

Master the skills of data science and business analytics and latch onto desirable opportunities with the certification course by IPL School of Data Science.

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5 Months

1,299 USD

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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

Data science has evolved into the most technologically advanced domain which has become a part of every organization. It is basically an interdisciplinary domain that uses multiple algorithms, scientific methods, processes, and systems to get the required knowledge from complex, structured, or unstructured data. Data being the most important thing in organizations must be protected and considered before taking any business development decisions. The course Become A Data-Driven Leader is a post-graduate program in data science and business analytics. It is provided by the IPL School of Data Science to all the students who wish to build their careers as data scientists or business analysts.

International Certification Program In Data Science And Business Analytics training is given by industry experts through online mode and there also be weekly interactive classes with one-to-one assistance from the faculty. This course is of 5 months duration and the candidate will be exposed to multiple projects and assignments for the overall development. The candidates can avail of multiple benefits through the portal for making learning easy and interesting. The enrolled students will also get International Certification Program In Data Science And Business Analytics certification from the IPL School of Data Science.

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The Highlights

5 months duration
5 capstone projects
Weekly live sessions by experts
Learning with library toolkits
One-to-one mentorship
Career Assistance
Access to career labs

Programme Offerings

7 Months Duration
Certification
One-to-one mentorship
weekly faculty sessions
Career Assistance
learning library with toolkits
hiring talentathons
CATAPULT data career labs

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Institute of Product Leadership, Bangalore

The IPL School of Data Science is allowing fees through credit card, debit card, and internet banking. Interested students can enroll in the course by clicking on the ‘Enroll Now’ button available on the homepage of the website.

Fee structure of International Certification Program In Data Science And Business Analytics

Name of the course	Fee in USD
International Certification Program In Data Science And Business Analytics	$ 1299

Eligibility Criteria

Work Experience

The candidate enrolling in International Certification Program In Data Science And Business Analytics should have at least 1 year of working experience in technical or business-related fields.

Certification Qualifying Details

International Certification Program In Data Science And Business Analytics is awarded by the IPL School Data Science to all the learners who shall complete the course. Enrolled candidates should complete the projects and assignments on time. The certification will open gates of opportunities in the domain of data science and business analytics.

What you will learn

Data science knowledgeBusiness analytics knowledge

International Certification Program In Data Science And Business Analytics certification syllabus is comprehensive and it is designed for the overall development of the learners. The course comprises 5 sub-courses in it for making learners proficient in the domain of data science and business analytics. Moreover, the candidate will gain skills in tools like Python, tableau, Microsoft-SQL-server, Jupyter, and excel.

The candidates will learn the following concepts during the course and shall become proficient in the domain.

Business Problem Framing,
Business Inferencing using statistical techniques,
Insight Mining,
Business Analytics,
Prescriptive & Predictive Analytics,
Exploratory Data Analytics and Feature Engineering,
Data Visualization, and Storytelling.
Data Analytics with Python.

Who it is for

Data AnalystData ScientistBusiness Analyst

International Certification Program In Data Science And Business Analytics benefits the people who have the required experience and wish to pursue data science and business analytics for their careers. The course shall also help people who are working on the following designations by enhancing their skills and knowledge.

Data Analyst,
Data Science Manager,
Technical Product Manager,
Data Scientist (beginners),
Marketing Analyst,
Business Analyst,
Quality Analyst.

Admission Details

To enroll yourself in the International Certification Program In Data Science And Business Analytics online course. Follow the steps mentioned below.

Step 1: Visit the portal of the IPL School of Data Science and search for the course, or directly click on the link to land on the page https://www.productleadership.com/programs/post-graduate-program-data-science-and-business-analytics/.

Step 2: The screen with the detailed introduction of the course shall be displayed on the IPL School of Data Science portal.

Step 3: Click on the tab “Apply Now” and sign up for the course.

Step 4: Complete the enrollment process by paying the Become A Data-Driven Leader certification fee.

Step 5: Start learning by attending Become A Data-Driven Leader classes.

The Syllabus

Course 1: DSC401F - Data Analytics Foundations

Statistical Data Analysis in Excel
- Descriptive Statistics & Probability
- Inferential Statistics & Hypothesis Formulation using methods like T-test, ANOVA, Chi-Square
- Sampling distributions, estimation
- Simple, Multivariate regression & Time Series
- A/B Testing
- Goodness of Fit
Data Analysis using SQL
- Introduction to DBMS
- ER diagram
- Schema design
- Key constraints & basics of normalization
- Joins
- Subqueries involving joins & aggregations
- Sorting
- Independent subqueries
- Correlated subqueries
- Analytic functions
- Set operations
- Grouping and filtering
- SQL Aggregate & Rank Functions
- SQL Analytics Functions

Course 2: BAN403F - Business Problem Framing

Problem Formulation
- Understanding, Framing the Problem, and Formulating a Hypotheses
- Asking the Right Question
- Framework for Problem Formulation
- Transformative Problem Formulation
Business Problem as a Data Science Problem
- Business Problem Solving with Data Science
- Scoping your Solution
- Planning the Analysis
Sourcing and Collecting Data
- What is Data Collection?
- Sources of Data
- Methods of Data Collection
- Process of acquiring, collecting, extracting, and storing

Course 3: DSC402F - Data Science Techniques

Exploratory Data Analytics and Feature Engineering
- Overview
- What is EDA?
- The EDA Workflow
- Characterizing Data
- Univariate and Multivariate Distribution Plots
- Univariate and Multivariate Comparison Plots
- Univariate and Multivariate Composition Plots
- Structuring your Report
- Extracting Features
- Demo Principal Component Analysis
- Factor Analysis
- Clustering
- Selecting Features
- Engineering Features
Data Analytics with Python
- Importing Datasets
- Cleaning the Data (Data Wrangling)
- Data frame manipulation. (Exploratory Data Analysis)
- Summarizing the Data
- Model Development & Evaluation (optional)

Course 4: DSC403F - Predictive and Prescriptive Analytics for Business Decision Making

Time Series Forecasting
- Introduction to Time Series
- Correlation
- Forecasting
- Autoregressive Moving
- Average (ARMA) models
- Autoregressive Integrated
- Moving Average(ARIMA) models
Simple and Linear Multiple Regression
- Simple Linear Regression and Multiple Linear Regression
- Regression Fundamentals
- The linear regression equation
- Linear Regression explained
- Linear Regression with independent variable
- Interpreting R -Squared
- Evaluating Model Performance
- Key assumptions of Linear Regression
- Residual Analysis
- Statistical tests to validate assumptions
- Correlation and Causation
- Heat map and Scatter plots
- Multiple Linear Regression use case
- Interpreting regression outputs
- Regression use cases

Course 5: BAN401F - Visualization and Storytelling

Data Visualization
- Introduction to Data Visualization
- Visualization in Business Analytics
- Introduction to Tableau
- Basic charts and dashboard
- Descriptive Statistics, Dimensions and Measures
- Visual analytics
- Dashboard design & principles
- Advanced design components/ principles: Enhancing the power of dashboards
- Special chart types
Storytelling with Data
- The Art of Storytelling in Business Analytics & Data Science
- Effective Data Storytelling for Business Impact
- Storytelling and the Human Brain
- Bringing Data to Life: Emotions and Data Storytelling
- Emotion Modulators: Color, Language and Other Design Elements
- Story Considerations
- Preparation of the story points
- Setting up the story
- Create a data story in a static presentation

Product Analytics and Metrics

Introduction to Product Analytics
- Product analytics definition
- Differences between product and “classic” web analytics
- Common questions and mistakes
Data Collection
- Where, when, and how to collect data correctly
- Data formatting and standards
- Implications of incorrect data
Tools for Analysis
- Overview of the tools available
- Gathering requirements and defining use cases
- Evaluating tools for your use cases
Metrics
- Customer Acquisition Cost, Customer Lifetime Value, Churn Rate
- Leading vs. lagging metrics
- Benefits and drawbacks of core metrics
- SaaS Metrics
User and Cohort Analysis
- How to understand users
- Cohort creation and analysis
- Sample user-based metrics used in product analytics
Reporting and Monitoring Product Metrics
- A selection of metrics for product analytics
- Setting up reporting and fundamental data visualization principles
- Setting up monitoring

Social and Web Analytics

Web Analytics: Understanding the metrics
- Which metrics can be monitored
- Which metrics matter and how they’re related
- How marketing strategy or editorial decisions are effected by web data
- Why SEO is relevant
Introducing: Social Media Measurement
- Introducing: Social Media Measurement
- Social Media Analytics: Subscribers, Engagement, Reach, Velocity and Sentiment
- Measuring Likes and Followers and Subscribers on Facebook, Twitter, Instagram
- What is Engagement and How to Measure Engagement on Facebook & Twitter
- Reach – Can Actual Exposure and Reach be Measured on Facebook and Twitter?
Social Media: Facebook Insights
- Post success – impressions, reach, engagement and the difference between them.
- Understanding Engagement – engagement metrics and how they relate to strategy.
- Tracking and understanding audiences – who are your followers and why, what is their reach and how it affects strategy.
- Downloading reports – how to track and measure analytics month-on-month.
Social Media: Twitter Analytics
- Tweet impressions v engagement and how to track success.
- Follower data and how to apply that to strategy.
Return on Investment
- Velocity in Social Media – Facebook Virality and Twitter Trends
- Marketing Intel and Social Media Measurement: Analytics and Psychographics
- Measuring ROI (Return on Investment) and the Ecosystem of Apps, widgets, mashups