Curriculum Review of Executive PGP in Data Science from upGrad

The article covers a detailed curriculum review of a popular upGrad data science course – Executive PGP in Data Science.

upGrad is among the most popular online platforms that have made its niche in the data science segment. It offers quality data science programs that many audiences can take up. This article will review Executive PGP in Data Science from IIIT Bangalore & upGrad. Read the article to know the upGrad data science course review, curriculum, projects covered, costs, and pros and cons.

Content – upGrad Data Science Course Review

• Course information
• Key Highlights of the Program
• Program Curriculum
• Industry Projects
• Detailed Course & Curriculum Review
• Why Should you take up Executive PGP in Data Science?
• Drawbacks
• Career Outcome
• Student Reviews

Executive Post Graduate Programme in Data Science from IIIT Bangalore – Top upGrad Data Science Course

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Course Information

Eligibility – Bachelor’s degree with 50% mandatory

Course Duration – 12 months

Course Fee – Rs. 2,99,000, starting at Rs. 6,907/month

Tools Covered – Python, Tableau, MySQL, Hive, MS Excel, PowerBI, MongoDB, Shiny, Keras, AWS, MapReduce, Spark, Hadoop, OpenCV, Airflow, HBase, and TensorFlow, among others.

Top Skills You Will Learn – Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data, and Natural Language Processing.

Job Opportunities: Data Analyst, Data Scientist, Data Engineer, Product Analyst, Machine Learning Engineer, Decision Scientist

Who is this program for: Engineers, Marketing & Sales Professionals, Freshers, Domain Experts, Software & IT Professionals

Instructors and mentors:

Key Highlights of the Program

Program Curriculum  

• Course 1: Data Toolkit 
• Course 2 – Machine Learning – I 
• Specialization – Deep Learning/Natural Language Processing/Business Analytics/Business Intelligence/Data Analytics/Data Engineering

Industry Projects

The program covers 18 real-life industry projects sponsored by top companies across industries, some mentioned below. 

IMDB Movie Analysis

Analyze movies from the past 100 years and find several insights into them using data manipulation and analysis techniques in Pandas.

Credit EDA Case Study

A case study on a real-world problem based on exploratory data analysis.

Clustering Assignment 

Use ML concepts to help an NGO make its plans for lagging countries.

Telecom Churn 

Help telecom companies identify and churn customers. Learn to implement Dimensionality reduction and Classification techniques.

Fraud Detection 

Build an ML model to identify fraudulent credit card transactions

Retail-Giant Sales Forecasting 

Help retail companies to forecast their sales

Hive Case Study 

Work on an e-commerce company data set and use your Hive and Hadoop learnings.

Bike-sharing systems (Linear Regression Assignment)

Build a model to understand the factors on which the demand for bike-sharing.

Lead Scoring

Help the sales team of your company identify which leads are worth pursuing. 

RSVP Movies (SQL Assignment)

In this assignment, you will work on a movies dataset using SQL.

ETL Project

This is an ETL project which will cover the topics like Apache Sqoop and Apache.

Assignment – Structured Problem Solving

This assignment will test the learner’s understanding of the previous 2 modules on structure problem-solving.

IPL Visualisation Assignment

Do an exciting assignment on sports analytics in Tableau

Advanced Regression

Build a regularized regression model to understand the most important variables to predict house prices in Australia.

NYC Parking: EDA using Apache Spark

Analyze the dataset of parking tickets.

MapReduce Programming Assignment

Practice MapReduce Programming on a Big Dataset.

Business Case Study – Staff Planning

Solve an industry case study using optimization techniques.

Assignment – Classification

Practice assignment & all resources related to a classification-based problem statement.

We would have liked the dataset sources mentioned in this upgrad data science course. It’s not clear if the data sets are from Kaggle, UCI Machine Learning Repository, Quandl, CERN Open Data Portal, Google Dataset Search, or any other platform. Suppose you compare it with the Post Graduate Program In Data Science by Simplilearn. In that case, you will find that it offers 3 capstones and 25+ Projects with industry data sets from Amazon, Uber, Walmart, Comcast, etc., at Rs. 2,55,800, giving it an upper hand.

Detailed Course & Curriculum Review 

HRAI says Executive PGP in Data Science is India’s number 1 online Data Science program. This upgrad data science course is aligned to competency standards developed by NASSCOM. Executive Post Graduate Programme in Data Science covers the basics of data science concepts and can be taken up by both freshers and professionals. Being a deadlines-focused course requires the course takers to focus and dedicate the required hours. It comprises scenario & coding explanations, conceptual questions, scenarios to code & case studies to help the course takers understand and practice the concepts.

Main Course Content

The course content is imparted through recorded and live sessions. To prepare you for the rest of the course content, a preparatory course covers tools like Python and Excel, so you will be prepared beforehand before digging deeper into data science and machine learning concepts.

You will then learn about the Data Toolkit, where the basics of Python and Programming, EDA, Inferential Statistics, Data Analysis using SQL, and Advanced SQ are covered. If you are from a non-technical background, then you can benefit from the 30-hour Python programming Bootcamp focuses on developing basic and intermediate Python programming concepts.

You will then move on to the next course, which is machine learning. You will learn about Regression, Classification using Decision Trees, Unsupervised Learning: Clustering, Basics of NLP and Text Mining, and Business Problem Solving. Specialized courses are available after you complete Course 2, where you can select from Deep Learning, Business Intelligence, Data Analytics, Data Engineering, Natural Language Processing, and Business Analytics. 

Must Explore – Data Science Courses

Specializations

Let’s take a look at these specializations individually and understand what they cover and what they miss out on –

Deep Learning 

It is an extension of the machine learning course and covers both the topics of ML and DL. You can choose this specialization if you want to move towards the image processing part. It covers popular algorithms like CNN, object detection, and image segmentation. We think that this course should be purely focused on DL topics. Extended topics like Bagging & Random Forest, Boosting, Model Selection & General ML Techniques, PCA, Advanced Regression, Advanced ML case Study, and Time Series Analysis, should have been covered in Course 2 – Machine Learning only so that anyone who is not choosing DL as a specialization does not miss these machine learning topics. 

Also, DL specialization misses out on certain topics like computer vision, algorithms like Long Short Term Memory Networks (LSTMs), Generative Adversarial Networks (GANs), GRU, Autoencoders, Transformers, YOLO V4, Mask RCNN, Detectron, etc.

Top Deep Learning Courses

It could have also covered case studies from healthcare (Covid), autonomous driving, sign language reading, music generation, and more project-oriented modules. A popular problem statement from Kaggle could have been included in the course. The specialization program would last 22 weeks, so expectations for course content quality and coverage go high. However, you will learn how to build a spell checker & spam detector using techniques like phonetic hashing and neural networks from scratch.

Natural Language Processing

Like the Deep learning specialization, NLP specialization also covers ML topics. I downloaded the Course Brochure to check for some errors on the website, but there wasn’t. NLP specialization also covers advanced ML topics, and NLP topic is touched on only after the 6 topics on advanced ML. 

The course includes topics like applying the concepts of DL in natural language processing problems through encoder-decoder architecture, NMTs, and implementing them in TensorFlow, and different techniques like word-embeddings and topic modeling. 

It is missing important NLP topics like Tokenization, Lemmatization, Stemming, N-gram, Named-Entity-Recognition (NER), Vectorization, and Inverse document frequency (TF-IDF), Attention Models, Hugging face transformers, etc.

Popular Online NLP and Text Mining Courses

Business Analytics 

I compared the business analytics specialization of the Executive Post Graduate Programme in Data Science from IIIT Bangalore to other programs like Post Graduate Certificate Program in Data Science from Simplilearn and PGP – Data Science and Business Analytics. I found this program to be more exhaustive. 

The business analytics portion is very nicely curated step-wise, starting from the basics of data visualization in Tableau to advanced Excel and PowerBI and then moving on to structured problem solving using frameworks like 5W, 5WHYs, and SPIN. The course material also includes data storytelling. 

We would have seen more BA techniques covered in the course content like SWOT Analysis, MOST Analysis, Business Process Modelling (BPM), Non-functional Requirement Analysis, PESTLE Analysis, Requirement Analysis, etc.

Overall, the course progression looks reasonable in the Business Analytics specialization. The specialization culminates in an interesting project involving Airbnb datasets to represent data storytelling and effectively help make important business decisions. 

Best Business Analytics Courses

Business Intelligence/Data Analytics 

If you choose to take up Business Intelligence/Data Analytics specialization, that can be an added advantage. Courses like Post Graduate Program In Data Science by Simplilearn, PG Program in Data Science and Business Analytics by Great Learning, and Post Graduate Certificate Program in Data Science by Edureka still don’t cover this subject in their PGP in data science. 

However, this upgrad data science course costs more than the above-mentioned programs, so it is expected to go the extra mile and cover some additional topics, including business intelligence/data analytics.

The first half of the course content is similar to business analytics specialization, whereas the second half covered more advanced problem-solving and programming. This part includes data structures – sets, dictionaries, stacks, queues, searching and sorting, algorithm analysis + recursion, advanced database programming using pandas, various programming questions in both SQL and Python in a timed environment, and ends in a capstone project.

Since they have designed a specialization in business intelligence, we hope they cover business intelligence tools like Power BI, Oracle Analytics Cloud, MicroStrategy, TIBCO Spotfire, Qlik Sense, datapine, SAS Business Intelligence, etc.

Data Engineering 

Data engineering is one segment mostly not covered in the curriculum of similar data science programs by other vendors. Adding data engineering to a core data science program can be innovative. It will make this course by IIIT-B a unique one, given the high demands for skilled data engineers in the data science and analytics field.

In this specialization, you will learn the concepts of Data Management and model data from a Relational Database, get an introduction to big data analytics, and learn about various big data applications. 

Then the specialization covers the concept of cloud, distributed data processing, and storage with Hadoop. You will learn how to set up your AWS account and write MapReduce jobs in Python, NoSQL databases, and Apache HBase. Get your hands dirty on designing a data warehouse and a data lake, and use Sqoop and Flume to ingest structured and unstructured data into Hadoop. 

Data engineering specialization further moves to AWS Cloud, Apache Hive, and querying and teaches how to deploy a Redshift cluster and use it for querying data. Learn to use Sqoop, Redshift & Spark to design an ETL data pipeline, real-time data processing using Spark streaming, build automated data pipelines with airflow, analytics using Pyspark, real-time data streaming with Apache Kafka, and end with a capstone project.

Top Data Engineering Courses

Why Should you take upGrad Data Science Course?

• 400+ content hours available 
• 57 live learning sessions and 20+ expert coaching sessions
• Career transition with a 57% average salary hike
• Weekend classes with top faculties of IIIT B
• Designed for working professionals
• IIIT Bangalore alumni status
• 14+ programming tools & languages and 60+ industry projects
• India’s 1st EPGP aligned to SSC NASSCOM competency standards
• Equivalent to NSQF (National Skill Qualification Framework) level 8 

Drawbacks 

• Huge batch sizes make it difficult for students to participate in live discussions.
• Less-efficient technical assistance, and a slower response cycle, according to some students’ reviews.
• Specializations like Deep Learning and NLP should have covered more trending and important topics.

Career Outcome 

Executive PGP in Data Science prepares you to work as data analysts, data scientists, product analysts, machine learning engineers, decision scientists, etc.

Student Reviews

So these were some good reviews; let’s move on to critical reviews of the course I found on Quora.

The below reviewer is a data scientist working in Wipro. She says –

Here is another screenshot from Quora; this reviewer is a career coach.

Conclusion – Top upGrad Data Science Course

Talking about this data science course review, the content of the upgrad data science course looks interesting. It has 1 capstone project (from specialization) and 18 projects. However, the course content could have been more exhaustive to give a holistic learning experience to the course takers.

Talking about the cost, you will have to pay Rs. 3 Lakh for this course. It can be feasible for working professionals but not freshers or college graduates. 

If you want to spend extensive time learning one of the different specializations available, then go for this upgrad data science course. But if you are a fresher or just exploring data science, I recommend you go through the free resources available and learn the concepts.