My honest review-Microsoft AI Professional Program. Review on Great Learning

This review provides insights into the "Microsoft AI Professional Program(AI to Open AI), " based on a recent participant's experience. The program aims to equip learners with AI knowledge, but certain aspects of its delivery and support warrant consideration before enrollment.

Key Takeaways from the Experience:

Areas for Improvement:

Timezone Incompatibility: Initial introductory sessions were scheduled at inconvenient times for participants in certain time zones, leading to missed opportunities for early engagement.

Delayed Technical Support: For those subscribed to Azure ML, technical assistance for lab issues was significantly delayed, with a reported turnaround time of 3-4 days. This hindered continuous learning and raised questions about the value proposition compared to more self-paced platforms like Udemy.

Reliance on Peer Support: While a WhatsApp group is provided for community interaction, the effectiveness of support within this group is highly dependent on the proactivity and enthusiasm of other participants.

Program Management Office(PMO) Responsiveness: The PMO's responsiveness reportedly shifted from proactive to reactive. A significant communication lag(6-8 hours) was experienced due to the assigned program manager operating in a different timezone(US vs. participant's local time), impacting timely resolution of inquiries. Although the PMO made efforts to connect, the utility of their responses was sometimes limited by these delays.

Program Depth: The program structure is primarily designed to cover concepts and introduce new topics rather than offering a deep technical dive. Self-exploration is highly encouraged, implying that learners need to be proactive in pursuing advanced understanding beyond the curriculum.

Positive Aspects:

Experienced Tutors & Interactive Sessions: A significant highlight was the tutoring, which came with sound real-time experience. Sessions were noted to be very interactive, fostering a dynamic learning environment.

Concept Coverage: The program effectively covers core AI concepts and helps participants become acquainted with new developments in the field.

Recommendations for Prospective Students:

Based on this experience, it is crucial to inquire thoroughly before committing to this program, especially if you anticipate needing technical assistance or prefer structured deep dives.

Assess Your Learning Style: If you are a self-starter and enjoy exploring topics independently, you might find the conceptual coverage sufficient. However, if you require extensive technical guidance and prompt support, consider alternative options.

Clarify Support Mechanisms: Before enrolling, explicitly inquire about the academic support turnaround times, especially for hands-on lab environments like Azure ML. Understand how technical issues are resolved and if timezone differences will impact your learning pace.

Evaluate Program Depth: If you already possess a strong understanding of Machine Learning(ML) and Deep Learning(DL) and are seeking advanced, in-depth topics, carefully review the program structure. Engage with sales representatives, asking specific questions about each module's technical depth and practical application, rather than making a decision after just a few conversations.

Explore Alternatives: It is highly recommended to explore other programs and providers to find one that aligns best with your learning objectives, technical support needs, and time zone.

Good luck with your learning journey!