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Post-Graduate Program in Data Science (PGP-DS)
BY
Amity Future Academy
Hone your analytics skill by joining the Post-Graduate Program in Data Science (PGP-DS) and master cutting-edge technologies driven by the power of data.
Online
12 Months
₹ 215,000
Inclusive of GST
Quick facts
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Learning efforts
7-10 Hours Per Week
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Course overview
The Post-Graduate Program in Data Science (PGP-DS) training is a 12-month online and, comprehensive study that provides you with both the theoretical and practical knowledge of various data science concepts. During training, candidates will master data analytics, machine learning, data visualisation, and deep learning, and technologies like R, Tableau, Hadoop, Python, Spark, Hive, and SQL. Amity Future Academy provides this course in partnership with New York-based Cornell University’s online education department, eCornell.
The Post-Graduate Program in Data Science (PGP-DS) certification course features dedicated career assistance, a virtual job fair, and recruitment platforms like Hiration and CutShort.io. Candidates also get access to four case studies by Harvard Business Publishing and projects, along with premier quality video lessons delivered by industry experts.
By the course end, you will undertake a capstone project, which aims to consolidate all the knowledge gathered during the online Post-Graduate Program in Data Science (PGP-DS) training course. Candidates receive a certificate after finishing all course modules, assignments, and capstone projects. eCornell also provides certification, 26 Professional Development Units (PDUs), and 40 Professional Development Hours (PDHs).
The highlights
- Personal mentoring sessions
- Certification from eCornell
- 24/7 access to course materials
- 12 months course
- Industry-based projects
- Live interaction with industry experts
- Alumni status for Amity Future Academy
- 7-10 Hours per week
- Career support and assistance
Program offerings
- Course-completion certificate
- Personal mentoring
- Case studies
- 24/7 access
- Hands-on training
- Capstone project
- Live interactive doubt solving
- Career assistance
- Ecornell certification
Course and certificate fees
Fees information
₹ 215,000
(Inclusive of GST) Post-Graduate Program in Data Science (PGP-DS) fee structure
Course | Amount |
Post-Graduate Program in Data Science (PGP-DS) | Rs. 2,15,000 |
certificate availability
Yes
certificate providing authority
Amity Future Academy
Eligibility criteria
Mathematics
Statistics
To enrol in the Post Graduate Program in Data Science (PGP-DS) online training, you must have a BE / BCA / B.Tech / MCA / B.Sc. (Maths) / M.Sc (Maths) degree with a minimum aggregate of 50%. A background in Mathematics or Statistics is preferred. Students must have a two-year work experience. Moreover, if you’re a deserving graduate or post-graduate with a GPA > 7/10, Amity Future Academy can relax the work experience criteria.
Certification Qualifying Details
Moreover, to get the Post Graduate Program in Data Science (PGP-DS) certification by Amity Future Academy, candidates will have to finish all the programme tests, assignments, modules, and quizzes. Moreover, you will also have to finish all the case studies and the capstone project at the end. The capstone project will be considered complete when you submit a detailed report on the project, along with a presentation.
What you will learn
R programming
Tableau knowledge
Knowledge of python
Knowledge of apache spark
Sql knowledge
Knowledge of big data
Knowledge of deep learning
By the end of the online Post Graduate Program in Data Science (PGP-DS) certification syllabus, you will be able to:
- Learn to develop procedures for data management, use data to drive vital business decisions, and make sense of illegible organisational data
- Determine how to combine predictive models and data visualisations with improving the accuracy of your predictions
- Learn to put together a business question in the form of a scientific hypothesis that can be evaluated using various statistical methods
- Formulate and verify regression models to learn the impact of attributes on a single decision and predict possible outcomes
- Gain proficiency in using a comprehensive range of software packages and statistical tools like R, Python, Hadoop, Spark, Excel, and MySQL
- Learn to perform visual analytics with paid software packages like Tableau, for which Amity provides a free subscription.
Who it is for
The Post Graduate Program in Data Science (PGP-DS) training provides comprehensive knowledge in the field of Data Science, and is a right fit for:
- Students in their final year of graduation
- Some professionals like the following:
- Data Analyst
- Data Scientist
- Big Data Analyst Engineer
- Big Data Developer
- Machine Learning Engineer
- Data Architect
Admission details
Please find the admission details for the Post-Graduate Program in Data Science (PGP-DS) classes:
Step 1: Open the Amity Future Academy’s website using this link- https://amityfutureacademy.com/Home/app/ and log in using your credentials.
Step 2: Browse the website’s ‘Program’ menu for the Post-Graduate Program in Data Science (PGP-DS) course.
Step 3: You will find the course under 12 months PGP certification program catalogue.
Step 4: Fill out the application form present at the top of the course page.
Step 5: You need to furnish the necessary details, including name, email address, contact number, country, and city of residence.
Step 6: Amity Future Academy will send you the login credentials via email.
Step 7: Now, you need to enter information about your current organization, work experience (in months), and educational qualification. Proceed to the next.
Step 8: Go through a screening call and share the final application with the office of the admission director.
Filling the form
To apply for the online Post-Graduate Program in Data Science (PGP-DS) course, submit the application form, available on the course webpage. An admission director from the Amity Future Academy’s office will call you for the screening process. The Admission Committee will make the final decision after reviewing your form and profile.
The syllabus
Module I - Introduction to Data Science
Mathematics for Data Science
- Probability and Inferential Statistics
- Linear Algebra
- Calculus
Introduction to R and Python
- Basic Python Programming constructs
- Functions and OOP in Python, NumPy basics
- Learn Pandas basic concepts, work with Series
- Work with Pandas DataFrame (Advanced)
- Fundamentals of R
- Univariate statistics in R
- Data preparation using R
Module II a - Data Visualization with Tableau
Introduction and Overview of Tableau
- Why Tableau?
- Why Visualization?
- Level Setting – Terminology
- Getting Started – creating some powerful
- visualizations quickly
- The Tableau Product Line
- Things you should know about Tableau
Getting Started with Tableau
- Connecting to Data and introduction to data source concept
- Working with data files versus database server
- Understanding the Tableau workspace
- Dimensions and Measures
- Using Show Me!
- Tour of Shelves (How shelves and marks work)
- Building Basic Views
- Help Menu and Samples
- Saving and sharing your work
Analysis
- Creating Views
- Marks
- Size and Transparency
- Highlighting
- Working with Dates
- Date aggregations and date parts
- Discrete versus Continuous
- Dual Axis / Multiple Measures
- Combo Charts with different mark types
- Geographic Map Page Trails
- Heat Map
- Density Chart
- Scatter Plots
- Pie Charts and Bar Charts
- Small Multiples
- Working with aggregate versus disaggregate data
- Analyzing
- Sorting & Grouping
- Aliases
- Filtering and Quick Filters
- Cross-Tabs (Pivot Tables)
- Totals and Subtotals Drilling and Drill Through
- Aggregation and Disaggregation
- Percent of Total
- Working with Statistics and Trend lines
Getting Started with Calculated fields
- Working with String Functions
- Basic Arithmetic Calculations
- Date Math
- Working with Totals
- Custom Aggregations
- Logic Statements
Formatting
- Options in Formatting your Visualization
- Working with Labels and Annotations
- Effective Use of Titles and Captions
- Introduction to Visual Best Practices
- Combining multiple visualizations into a dashboard
- Make your worksheet interactive by using actions and filters
- An Introduction to Best Practices in Visualization
Module II b - Understanding and Visualizing Data
- Learn to utilise your decision-making frameworks to achieve favourable outcomes
- Assess decisions by looking at KPIs and determining their impact on stakeholders
Module III -Predictive Analytics and Optimization Techniques
- Implementing Scientific Decision Making
- Case Study
- Using Predictive Data Analysis
Module IV - Machine Learning (Supervised Learning) - I
Regression Techniques
- Linear & Multiple Regression
- Support Vector Regressor & Decision Tree Regressor
- Hands-on Regression techniques
Data exploration
- Data Pre-processing
- Data Transformation
- Data Reduction
Evaluation methods
- Hold-out method
- Cross-validation and bootstrapping method
Classification Techniques
- Ensemble Methods
- Decision Trees
- Support Vector Machines
- K Nearest Neighbours
- Logistic Regression
- Naïve Bayes
- Hands-on classification techniques
- Case Study
Module V - Machine Learning (Unsupervised Learning) – II
Clustering
- Hierarchical clustering
- K-Means
- Proximity Measures in Machine Learning
- DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
Anomaly Detection
Dimensionality Reduction
- Need for dimensionality reduction
- Principal Component Analysis (PCA)
- Singular Value Decomposition (SVD
- T-distributed Stochastic Neighbor Embedding (t-SNE)
Association Rule Learning
- Apriori Algorithm
- FP growth
- Hands-on on clustering
- Hands-on association rule mining
- Hands-on dimensionality reduction
- Hands-on anomaly detection
- Case Study
- Database Management Systems
Module VI - Database Management Systems
Module VII- Deep Learning
Neural Networks
- Artificial Neural Networks (ANN)
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Long Short-Term Memory (LSTM)
- Gated recurrent units (GRUs)
Natural Language Processing (NLP)
- Case Study
Module VIII- Big Data Analytics
- Introduction to Big Data and Hadoop
- HDFS and YARN
- MapReduce and Sqoop
- Basics of Hive and Impala
- Working with Hive and Impala
- Types of data formats
- Advanced Hive Concept and Data File
- Apache Flume and HBase
- Pig
- Basics of Apache Spark
- RDDs in Spark
- Implementation of Spark Applications
- Spark Parallel Processing
- Spark RDD Optimization Techniques
- Spark Algorithm
- Spark SQL
- Case Study
Capstone Project
How it helps
Find the Post-Graduate Program in Data Science (PGP-DS) certification benefits mentioned below:
The global market is witnessing a two-times surge in demand for Data Analytics professionals. According to industry insights, the requirement will increase exponentially since around 70% of the organisations are planning on hiring Data Professionals in the upcoming years.
After completing the Post-Graduate Program in Data Science (PGP-DS) training course by Amity Future Academy, provided in collaboration with eCornell, you will master data analytics, business intelligence, data science, machine learning, and data engineering. Candidates will find jobs in companies like Google, Amazon, Zomato, Bewakoof, and more.
Instructors
Mr Ashish Gilotra
Instructor
Freelancer
M.E /M.Tech.
Dr Suresh Varadarajan
Instructor
Freelancer
Ph.D
Mr Naveen Bhansali
Data Analyst
Dell
Ms Sakshi Babbar
Instructor
Freelancer
Dr Mohit Kumar Goel
Instructor
Freelancer
B.E /B.Tech, Ph.D
Dr Karthic Narayanan
Instructor
Freelancer
Ph.D
Mr Tushar Kakkaiya
Instructor
Freelancer
FAQs
What is the difference between the job responsibilities of a Business Analyst and Data Science professional?
A business analyst draws out meaningful insights from various data sources and data sets. In contrast, data scientists strive to forecast future events or trends based on patterns observed in the past.
Which companies recruit data science professionals?
On successful culmination of the programme, you will be able to apply and get hired in companies such as Amazon, Walmart Labs, BrowserStack, Accenture, Google, and many more.
What topics will I learn during the Post-Graduate Program in Data Science (PGP-DS) online course?
The PGP-DS programme provides in-depth knowledge of concepts like visual analytics, machine learning, Artificial Intelligence (AI), deep learning, predictive analytics, big data analytics, and data-driven decision making.
Can I only register for a few modules and still earn a certificate?
No, you will have to opt for and complete all modules to earn a certificate.
Is there a deferral policy for the programme?
Yes, a deferral to the next batch of the programme is possible upon the approval of the Admission office.
