upGrad vs Udemy Data Science Course Reviews…Which To Choose?
upGrad vs Udemy Data Science Course Reviews
Comparing between UpGrad and Udemy to learn Data Science can be a daunting task. There are two platforms both of which are popular in the context of e-learning, with different characteristics that encompass course structures, fees, highlights, and students’ feedback.
UpGrad is focused on the implementation of the knowledge with relevant projects and also provides intensive career support with placement services. On the other hand, Udemy offers a comprehensive and flexible course that that aims at Data Science and offers it in lifetime access with activity-based exercises.
In this comparison, you will find all the information about the courses offered, fees structure, important aspects, and students’ reviews to facilitate your decision for the Data Science course with either UpGrad or Udemy.
upGrad Data Science Course: Courses, Key Highlights, Syllabus, Placements, Fees, Reviews
upGrad Data Science Course: Courses
One of the significant points that should be taken into account when deciding on the upGrad for the Data Science education is its focus on the longer course’s length and relatively higher prices compared to other educational platforms. However, what makes upGrad stand out from the rest is the well-stock array of features such as the Post Graduate Programs and collaborations with renowned universities from across the world. Such collaborations make a certain that students get value oriented curricula that aims at making the students job competent.
The company upGrad in its portfolio provides a range of programs in different fields that include MBA, Data science and analytics, the artificial intelligence, and machine learning, etc. If you want to advance in the corporate world, pursue a master’s degree, or attend an intensive BootCamp, upGrad has programs to meet any educational scenario. Thus, students gain opportunities to learn from the specialists of the industry who are more involved in the learning process, making it effective and informative.
upGrad Data Science Course: Key Highlights
| Attribute | Details |
|---|---|
| Generative Artificial Intelligence Integration | Courses include AI components to stay updated with industry trends. |
| Real-World Projects and Case Studies | Hands-on experience with projects that reflect actual industry challenges. |
| Placement Assistance | Dedicated support to help learners secure jobs after course completion. |
| 1:1 Mentorship Sessions | Personalized guidance from industry experts to enhance learning and career development. |
| Exclusive Job Portal Access | Access to a specialized job portal with significant opportunities and potential salary hikes. |
upGrad Data Science Course: Syllabus
| Module | Sub-Modules / Topics |
|---|---|
| Foundation Modules | |
| Introduction to Data Science | Overview of data science concepts and the industry. |
| Mathematics for Data Science | Basic mathematics, statistics, and probability essential for data science. |
| Programming Basics | Introduction to Python and R programming languages. |
| Data Handling | Techniques for data cleaning, preprocessing, and transformation. |
| Core Data Science Modules | |
| Data Analysis and Visualization | – Exploratory Data Analysis (EDA) – Data visualization using tools like Matplotlib, Seaborn, and Tableau |
| Machine Learning Fundamentals | – Supervised Learning: Linear Regression, Logistic Regression – Unsupervised Learning: Clustering, Principal Component Analysis (PCA) – Reinforcement Learning basics |
| Advanced Data Science Modules | |
| Deep Learning and Neural Networks | – Introduction to Neural Networks – Convolutional Neural Networks (CNN) – Recurrent Neural Networks (RNN) – Transfer Learning |
| Natural Language Processing (NLP) | – Text Mining – Sentiment Analysis – Word Embeddings – Advanced NLP techniques |
| Big Data Technologies | – Introduction to Big Data – Hadoop and Spark – NoSQL Databases |
| Specialized Modules | |
| AI and Machine Learning Applications | – Predictive Modeling – Time Series Analysis – Recommendation Systems |
| Business Analytics | – Data-Driven Decision Making – Business Metrics and KPIs – Case Studies in Business Analytics |
| Capstone Projects | – Real-world projects – Hands-on experience with industry datasets |
| Tools and Technologies | |
| Programming Languages | Python, R |
| Data Handling | MySQL, Pandas, NumPy |
| Machine Learning Libraries | Scikit-learn, TensorFlow, Keras, PyTorch |
| Data Visualization | Matplotlib, Seaborn, Tableau, Power BI |
| Big Data | Hadoop, Spark |
| Database Management | SQL, NoSQL |
| Capstone Projects and Industry Projects | – Real-world Scenarios: Work on projects from various industries like finance, healthcare, e-commerce, and more – Guidance from Mentors – Portfolio Development |
upGrad Data Science Course: Placements
UpGrad provides great placement support
- 57% Average Salary Hike: Significant salary increase post-course.
- Highest Salary Offered: ₹1.23 Cr per annum.
- 6000+ Career Transitions: Successful career changes for many learners.
- 300+ Hiring Partners: Top companies like Amazon, Microsoft, and Tata.
upGrad Data Science Course: Fees
Fees vary by program and university
- MS in Data Science (Liverpool John Moores University): ₹3,00,000 to ₹5,00,000.
- Post Graduate Programme in Data Science & AI (IIIT Bangalore): ₹2,50,000 to ₹4,00,000.
- Data Science Bootcamp: ₹1,50,000 to ₹2,50,000.
upGrad Data Science Course Fees
upGrad Data Science Course Reviews
The learners also appreciate upGrad for the rich content of the program, practical assignments and quality of trainers. The best aspects are, indeed, placement assistance and support from mentors. Its Data Science courses are evidently lucrative with graduates testifying to a successful career switch and increase in remunerations.
Success Stories:
- Abhinay Bandaru: The configurational analysis shows that the following specific configurations were instrumental in learning: The mentors who helped me understand new things that I came across.
- Bhagvathi: I particularly got a job as Data Analyst at Kantar with the help of upGrad’s content and placement drive.
- Moulik Srivastava: ‘The ability to engage in projects and to be mentored was proven to be very effective.’
- These programs are recognized for high academic affiliation coupled with an emphasis on the operations aspect and extensive career support hence upGrad’s Data Science programs are ideal for a professional seeking upward mobility.
Udemy Data Science Course: Courses, Key Highlights, Syllabus, Placements, Fees, Reviews
Udemy Data Science Course: Courses
Udemy’s “The Data Science Course: “Complete Data Science Bootcamp 2024” belongs to the popular Udemy courses and is focused on the comprehensive training in data science. While other similar and even cheaper programs can be obtained at AnalytixLabs or other institutions, this and other Udemy courses are perfect for everyone from novices to those who want to upgrade their knowledge.
This course offers a large variety of materials and consists of the basics of Data Science, AI, and Machine Learning divided into lessons. They include the real-life coding activities, case studies, and the real observation that the students get in taking the course as a means of preparing the students’ interest for real life applications in the job market. Constant assistance from the active users, coupled with lifetime membership to Udemy provides the learner all the necessary tools to deal with real life challenges in the field of data science.
Udemy Data Science Course: Key Highlights
| Attribute | Details |
|---|---|
| Comprehensive Coverage | Extensive curriculum that includes all essential data science topics. |
| Practical Coding Exercises and Case Studies | Includes hands-on coding exercises and real-life business case studies to enhance practical skills. |
| Step-by-Step Installation and Setup Instructions | Provides detailed guidance on how to install and set up required software. |
| Active Q&A Support and Community Engagement | Offers ongoing support through Q&A sessions and engagement with the course community. |
| Access to Future Updates and Additional Resources | Learners receive updates and additional resources as they become available. |
| 30-Day Money-Back Guarantee | Provides a risk-free trial with a guarantee of a full refund within 30 days if not satisfied. |
Udemy Data Science Course: Syllabus
| Module | Topics |
|---|---|
| 1. Introduction to Data and Data Science | – Big Data – Business Intelligence (BI) – Business Analytics – Machine Learning (ML) – Artificial Intelligence (AI) |
| 2. Mathematics | – Calculus – Linear Algebra |
| 3. Statistics | – Statistical Analysis – Hypothesis Testing |
| 4. Python Programming | – Python Basics – Libraries: NumPy, pandas, matplotlib, Seaborn |
| 5. Data Visualization | – Tableau – Data Storytelling |
| 6. Advanced Statistics | – Regressions – Clustering – Factor Analysis |
| 7. Machine Learning | – Supervised and Unsupervised Learning – Model Evaluation – Hyperparameter Tuning |
| 8. Deep Learning | – Neural Networks – TensorFlow |
Udemy Data Science Course: Placements
Even though Udemy doesn’t provide direct placement services, finishing this course will provide you with the skills and knowledge needed to apply for jobs in data science. The course contains projects and real-world business case studies that you may add to your portfolio to increase your employability.
Udemy Data Science Course: Fees
Udemy Data Science Course Fees
Udemy Data Science Course Reviews
The course has received a good rating of four. 6 out of 5 from 142,118 people. Concerning the strength, the identified strength include the provision of comprehensive content, integration of practical exercises and the effective organizational of the content to teach the learners complex concepts. However, from the learners’ perspective, some have suggested that more reinforcement on some of the covered machine learning methods like Random Forest and Support Vector Machines would complement the course.
Featured Review
Janaki Ballav Mohapatra: As always, 365 careers is fantastic. I loved the Deep Nets part mostly. However, there are other significant Machine Learning techniques such as Random Forest Classification/Regression and Support Vector Machines/Regression I wish were covered. Nonetheless, the course is exceptional, which covers almost everything. Thank you 365 team, you all are simply the best. Janaki Mohapatra, India
This course is good for those who wish to become a data scientist or those who want to learn the upgraded version in data science and related careers.
upGrad vs Udemy Data Science Course Reviews: Differences
| Feature | upGrad | Udemy |
|---|---|---|
| Course Structure | Structured with foundational, core, advanced, and specialized modules | Flexible, self-paced, broad topics in one course |
| Certification | University-affiliated certifications | Udemy certificate of completion |
| Practical Experience | Real-world projects, capstone projects, industry case studies | Practical exercises, but less extensive |
| Mentorship | 1:1 mentorship from industry experts | Community support, no personalized mentorship |
| Placement Support | Placement assistance, job portal access, career support | No direct placement services |
| Cost | Higher, reflects comprehensive program and support | Lower, more affordable |
| Flexibility | Fixed schedules and deadlines | Self-paced learning, flexible timing |
Conclusion
If one is looking to make a class-selection between upGrad and Udemy for a Data Science course, it entirely depends on the prospect’s requirements. If you are looking for a systematic program, which is recognized by the university, extensive one on one mentorship and placement, upGrad is a good option. On the other hand, if you are ok with looseness, open price range, and if more self-driven style is enticing to you, then Udemy’s courses provide credible content and skills training
Each of them has advantages, and the best one will match your approach to learning, goals, and wallet.
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