UPGRAD-data-science-bootcamp
Greetings to all, today we will discuss the elements of the upGrad Data Science Bootcamp Course Review that upGrad offers. The field of business schooling has experienced tremendous growth, providing students with additional opportunities to excel in their chosen fields. As you can see, there are many businesses and organizations to investigate when we enroll in a business course. Let’s now recognize the importance and merit of this course and why you should consider enrolling in it.
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UpGrad was founded in 2015, its creators had a vision that they wanted to help students get the knowledge they needed outside of the classroom to get ready for the workforce. Since its establishment, UpGrad has grown into a multi-platform that offers a vast array of course types and levels. It also partners with top universities and modern industry professionals to provide a wide range of courses taught by certified instructors with in-depth knowledge in a variety of sectors. Their teachers are personally chosen from among the subject matter specialists and possess extensive training in that particular area! Phalgun Kompalli, Mayank Kumar, and Ronnie Screwvala are the inventors of UpGrad.
It keeps providing excellent service to all the students and has established itself as one of the biggest e-learning platforms in India. Let us go no further and jump into the main plot.
Here we shall solely concentrate on this course and try to understand each aspect of the course.
Here are the first few classes and their highlights
Module | Title | Topics Covered | Tools Covered |
---|---|---|---|
Module 1 | Fundamentals | – MS Excel fundamentals | – MS Excel |
– Formatting concepts | |||
– Statistical analysis using Excel | |||
– Basic programming concepts (algorithms, loops, flow charts) | |||
– Overview of computers, operating systems, and the World Wide Web | |||
Module 2 | Data Analysis | – SQL Basics | – SQL |
– Python for Data Science (installation, basics, functions, files, OOP) | – Python | ||
– Descriptive Statistics, Distributions, and Probability Theory | – Pandas, NumPy | ||
– Hypothesis Testing, Regression, and ANOVA | – Matplotlib, Seaborn | ||
– Data Preprocessing, Web Scraping, and Exploratory Data Analysis (EDA) | – Plotly | ||
– NoSQL | |||
– Data Visualization with Tableau | – Tableau | ||
Module 3 | ML with Python | – Linear algebra and calculus applications in Data Science | – Python |
– Machine Learning (Linear Regression, Logistic Regression, KNN, Naive Bayes, SVM) | |||
– Regularization techniques (LASSO and RIDGE) | |||
– Decision Tree, Random Forest, and Boosting | |||
– Unsupervised learning (Clustering, PCA) | |||
Module 4 | Data Engineering | – Big Data Processing with Hadoop | – Hadoop |
– Streaming Big Data with Spark | – Spark | ||
– Machine Learning Model Deployment on Cloud | – AWS | ||
Module 5 | NLP & Deep Learning | Discovering NLP – Feature Extraction, Texblob, Spacy, Text Classification Grasping NLP – Sentiment Analysis and Chatbots | |
Module 6 | Data Structures & Algorithms | Basic Techniques of Algorithm Analysis Linked Lists and Binary Trees | |
I hope this helps! If you still need more in-depth take a look at the syllabus copy
Course Creators
Instructors
Here are the available projects for students to explore
Project | Description | Skills Learned |
---|---|---|
NutriGro | Build intelligence to predict user’s healthiness based on past grocery orders and recommend healthier options. | – SQL |
– Numpy | ||
– Pandas | ||
+2 (unspecified) | ||
AnomaData | Build intelligence to understand the health of machinery using Machine Learning and predict anomaly data/events. | – Linear Regression |
– LASSO | ||
– RIDGE | ||
+3 (unspecified) | ||
MoodForMusic | Building an application that detects the mood using still images or videos and recommends the music accordingly. | – Clustering |
– PCA | ||
– SQL | ||
+2 (unspecified) |
This is the course structure and how upGrad proceeds with its course
Product/Service | Description | Original Price | Discount | Final Price | Payment Options | Additional Information |
---|---|---|---|---|---|---|
Data Science Bootcamp | TailIcon model with scholarship or course | INR 1,55,000 | 47% off | INR 82,150 | – Pay upfront: INR 72,850 | – Additional scholarship up to 10k for “pay upfront” |
– Pay after placement: 8% CTC after landing a tech job | – EMI plans available |
Here’s the upGrad Data Science Bootcamp Course Review from alumni’s
Amazing Experience!
To the learners like me who joined the course as beginners in the tech domain, I’d like to convey a message – you don’t have to lose or be low on confidence just because you are a beginner. I assure you that upGrad has all the relevant content that you need to follow. I have myself given more than 50+ interviews, out of which I got rejected 23 times. Don’t lose hope. Understand what you did wrong, make notes with the help of the course content, and implement your learnings. Once I did that, I got offers from 15+ companies. The key is to not lose hope or confidence and keep practicing.
Bhupendra Choudhary
After 8 years of journey, I have always been looking for continuing my studies. Then after comparing through multiple options, I finally chose Upgrad because of the flexible timings and reviews from my colleagues. With Pandemic grasping the nation, and work from home changes in life, studying was not so easy. But with support from my family and experts at Upgrad, I was able to learn so many things. Upgrad has provided a path to learn, support for profile building and many other opportunities that will help me in transition in the field of Data Science.
Vaibhav Sah
Check Out- SCALER DATA SCIENCE COURSE REVIEW
Take up this course if you are ready to put in your effort and it is worth the time!
Prerequisites for the Data Science Bootcamp are nonexistent. Learners can join up for this boot camp, which offers best-in-class instruction, lots of practical exercises, and assignments using Cloud Lab, even if they have no prior programming or analytics experience.
Yes, any form of work experience, irrespective of the roles you are currently in, will be considered as work experience.
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