Liora

I found the curriculum disorganized and rushed, with projects assigned way too early in the process. In a group project meant for 3-4 people, I was forced to work alone because one groupmate showed complete disinterest while another, despite the intermediate level of the course, not only lacked basic skills—unable even to use Microsoft Word—the first one resorted to verbally abusive behavior in front of the instructor and Datascientest did nothing against that. This reckless approach to grouping and timing not only undermined the learning experience but also created an environment that was both unproductive and unnecessarily stressful. It has been 5 months since I completed the course, I still do not have the diploma they promised. I was supposed to use that for job applications but I could not. I am now employed to a completely unrelated field to datascience and I may have wasted 4 months doing this course. I did not get any employment assistance from this course provider. 3-4 months of bootcamp will not make anyone emplyoeable in datascience...

I just completed a very intensive Data Analyst bootcamp training course at DataScientest. The training is of high quality and the methodology is ideal for learning. It is "learning by doing". For each module, we learn by coding in Jupyter Notebooks or by creating Dashboards on various software: PowerBI, Looker Studio, Tableau. The core project carried out in groups during the training really allows us to put into practice all the knowledge and skills related to the training. It is a complete Data Science project that serves as a real experience!

Course Attended: Machine Learning and MLOps Course

Pro:
1. Certification from University Pantheon Sorbonne
The course provides a certificate from the prestigious University Pantheon Sorbonne, offering a valuable credential for career growth. This is a major attraction for prospective students.

2. Flexible Learning Structure
The online format, combined with self-paced study materials, allows for flexibility—ideal for individuals managing multiple responsibilities.

3. Networking Opportunities
The course encourages professional networking, offering tips to help students connect with others in the fields of machine learning and MLOps. The shared learning environment fosters valuable professional relationships.

4. Constructive Exam Feedback
The course includes shared exam corrections, which provide insights into common mistakes and alternative approaches, enhancing the learning experience.

5. Includes a comprehensive practical project at the end, allowing students to apply their learning in a real-world, hands-on context.

Cons:
1. Course Content and Quality
- Localization Issues: The course materials frequently contain typos, grammatical errors, and poorly translated sections. Some content appears to be direct translations from French, which sometimes include untranslated French text, making comprehension difficult for non-French speakers.
- Incomplete Curriculum: Critical topics, like the Central Limit Theorem in statistics, are missing from the curriculum. Such gaps leave students without essential foundational knowledge.
- Limited Practice Opportunities: There is a lack of preparatory exercises for exams, which limits the ability of students to properly practice and feel prepared.
- Inconsistent Language Delivery: Despite requesting English versions of course materials twice, some lectures and notes were still delivered in French. This inconsistency in language delivery demonstrates poor responsiveness and engagement.
- Poor English Proficiency: Some instructors have limited proficiency in English, making their explanations unclear and hard to follow.

2. Exam Structure and Support
- Short Exam Durations: Exam times are unrealistically brief, which prevents students from adequately demonstrating their knowledge.
- Generic Feedback: Feedback after exams is vague and lacks actionable details, hindering students from clearly identifying areas for improvement.
- No Exam Preparation Resources: The absence of targeted preparatory exercises adds unnecessary difficulty to the exam process. Students are allowed to take the exam multiple times, enabling them to access the questions online, review them after an initial failed attempt, and then retake the exam with prior knowledge of the questions. This practice, known and even encouraged by the instructors, significantly undermines the integrity and effectiveness of the evaluation process. 

3. Scheduling and Timing Issues
- Frequent Delays: Important meetings, including introductory sessions, often start 5-10 minutes late, which suggests poor time management and professionalism.
- Inconvenient Timings: Some live sessions are scheduled late in the evening, sometimes extending until 7:30 PM, which can be challenging for students with other commitments.

4. Technical and Administrative Shortcomings
- Technical Disruptions: Frequent technical issues disrupt the learning process, reducing the overall value of the course.
- Low-Quality Certificates: Intermediate certificates are poorly formatted, with overlapping text and QR codes, making them appear unprofessional and diminishing their value.

5. Pricing and Transparency Concerns
Pricing Discrepancies: Applicants using Germany's Bildungsgutschein are charged approximately €4,000 more than other students. This difference is attributed to supposed "extras" that do not justify the cost.

Questionable Extras:
- Extended Platform Access: Marketed as a benefit, but this should be standard for a course costing €13,500.
- AWS Course Access: The AWS courses included are publicly available for free, adding no real additional value.
- Integrity Concerns: The inflated pricing and lack of transparency raise serious questions about the program's integrity, especially given the marginal value of the supposed "extras."
- Ignored Price Adjustment Requests: Despite requesting a price adjustment to meet the €10,000 limit set by Agentur für Arbeit, the provider was unwilling to accommodate. The insistence on maintaining inflated pricing for superficial "benefits" like extended platform access and free AWS courses reflects a disregard for students' needs.