At ZCHPC, we understand the growing demand for skilled data analysts in organizations across Zimbabwe and beyond. That’s why we have meticulously crafted our Big Data Analytics Professional Certificate to equip you with the necessary skills and knowledge to excel in this field. Whether you are a recent graduate or a seasoned professional seeking career advancement, our comprehensive curriculum will help you stay ahead in the dynamic world of data analytics.

What sets our program apart is our blended learning approach, which combines the flexibility of online modules with the benefits of face-to-face interactions during physical classes. We believe in providing a learning experience that adapts to your schedule and preferences. With a minimum of 36 hours of contact time, spread over 3 hours per week, you can complete the program in just 3 to 6 months, depending on your pace.

Our esteemed instructors will guide you through eight modules designed to build your expertise from the ground up. The journey begins with an Introduction to Data Analytics, where you’ll gain insights into the practices, processes, and analytical skills essential for a junior or associate data analyst. From there, you’ll explore Data-Driven Decisions, learning effective questioning techniques and how to present findings to drive informed decision-making.

Preparing and Pre-Processing Data will teach you how to collect, organize, and ensure the credibility of data. You’ll delve into the art of data cleaning techniques and discover the power of SQL and spreadsheets in handling complex datasets. The Analyze Data to Answer Questions module will equip you with statistical analysis tools, while Share Data Through Visualization will empower you to create compelling narratives and visualizations using tools like Tableau.

To further enhance your skill set, we offer a dedicated module on Data Analysis with R Programming. You’ll explore the benefits of using the R programming language, master data manipulation techniques, and unleash the power of visualizations using RStudio and the Tidy verse package. Finally, you’ll complete a Data Analytics Capstone project, allowing you to apply your newfound knowledge to a real-world case study and showcase your abilities to potential employers.

Upon successful completion of the program, you’ll receive an internationally recognized certificate from ZCHPC and HEXCO, validating your skills and knowledge in data analysis. This certificate will open doors to a wide range of career opportunities, including roles such as Junior Data Analyst, Data Scientist, HR/Payroll Analyst, Finance Analyst, and many more.

At ZCHPC, we are committed to providing you with a transformative learning experience. Our dedicated instructors, coupled with hands-on exercises and access to cutting-edge tools, ensure that you gain practical skills that are immediately applicable in the industry. You will also have the opportunity to network with professionals in the field and stay connected with the latest trends and developments in data analytics.

Join us at ZCHPC and embark on a journey that will transform your career. Take the first step towards becoming a proficient data analyst by enrolling in our Big Data Analytics Professional Certificate. Unleash the power of data and unlock limitless possibilities in your professional journey. Together, let’s shape the future through data analysis excellence.

#ZCHPC #BigDataAnalytics #ProfessionalCertificate #DataAnalysis #EmpoweringProfessionals #TransformingCareers

#ZCHPC #EDTECH #VirtualRealityinEducation #EnhancingEducation #MutareHillcrestCollege #Innovation

The event concluded with the signing of a memorandum of understanding (MoU) between ZCHPC and Afrosoft, formalizing their commitment to collaborate on research, development, and knowledge exchange. This MoU marked the beginning of an exciting chapter in Zimbabwe’s technological journey, fostering a collaborative ecosystem that would drive innovation and uplift the nation. The Zimbabwe Centre of High-Performance Computing and Afrosoft’s partnership ceremony not only celebrated the union of two influential entities but also laid the foundation for a future marked by technological excellence and groundbreaking achievements according to 5.0 education constitution. With their combined expertise and resources, ZCHPC and Afrosoft are poised to revolutionize the technological landscape of Zimbabwe and make significant contributions on the global stage.

The Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development on the 13^th of April 2023 held the Presidential Awards Ceremony at HICC to present awards to students from institutions of higher and tertiary education who won prizes in 2022 global competitions.

Zimbabwe sent eighteen students who participated in the National Student Cluster Building Competition Program to India for the UNESCO-India-Africa Hackathon program with a representative from the Ministy Mrs Maria Adriano and three mentors from Zimbabwe Centre for High Performance Computing namely Priscilla Handikatare, Vimbainashe Masoso and Simba Nyamudzanga.

Fadzai Dzehonye from NUST receiving her award from the Honorable Minister Professor dr A. Murwira

Students from Harare Institute of Technology, University of Zimbabwe, Great Zimbabwe University, National University of Science Technology, Chinhoyi University of Technology and Midlands State University were selected.

The UNESCO INDIA – AFRICA Hackathon 2022 is an annual 36 hours nonstop event that brings together students, educators, teachers, and the research community of India and its African partners to tackle the common challenges faced by their countries and serves as a facilitator for cultural amalgamation. Twenty-two (22) African countries participated with a total number of hundred (100) mentors and a total number of six hundred and three (603) students where one hundred and sixty (160) were female and four hundred and forty-three (443) were male students.

Five students from Zimbabwe managed to scoop gold medals. These are Frank Makeba from Chinhoyi University of Technology, Besta Sibanda from National University of Science and Technology, Nyasha Mandizvidza from Great Zimbabwe University, Musindo Kahonde from Midlands State University and Daniel Chembesi from National University of Science and Technology .

Students with the Honorable Deputy Minister and the Ambassador

Prize giving ceremony

It is part of the ZCHPC mandate to train students on new technologies so that they can be innovative in support of the education 5.0^. The students met and shared knowledge with other students from around the world during the educational hackathon.

The Hon Minister of Higher and Tertiary Education, Innovation, Science and Technology Development Pror dr A. Murwira observes a ZCHPC COVID-19 Spread Regulator Robot

The Hon Minister of Higher and Tertiary Education, Innovation, Science and Technology Development Pror dr A. Murwira observes ZCHPC moving robots

ZCHPC robot picks water for Hon Minister of Higher and Tertiary Education, Innovation, Science and Technology Development Pror dr A. Murwira

The Hon Minister of Higher and Tertiary Education, Innovation, Science and Technology Development Pror dr A. Murwira gets water to drink using a ZCHPC robot

The importance of robotics was outlined clearly and the reasons to have robotics in developing countries were also outlined. The equipment and electronic components were placed on a working desk and students were guided on how to design a unique robot.
On the second day the students were assigned to do the design and assemble the robotics components with the help of distributed fascinators’ help on student formulated groups. Each group was focusing on a module of the whole robot and the modules were meant to be combined for form one complete and functional robot that can carry items from one point to the other. Facilitators helped students on challenges and questions pertaining the design of individual parts and the assembling of sub-modules to form one robot. For instance, facilitators helped to troubleshoot the problem with the controlling device.

Students were continuously reminded about teamwork and how it will contribute to their success as a group. During the workshop the students showed growing interest as they learnt more about Robotics and their abilities. Towards the end of the workshop the General Manager and other lecturers came and witnessed what their students were learning. The General Manager after hearing from the students just how much they learnt, was more than willing to sponsor the students with Robotics kits so that they can continue to improve their skills.

In conclusion, robotics training at TelOne went well and the students managed to produce a functional robot that could carry light items from point A to point B. Students and the General Manager were impressed with the knowledge shared with them and they felt that there is need for additional days where advanced robotics trainings should be done.

Visualize the events in a video available at https://youtu.be/EPhJ6sT2xy0

 The Benefits

Participation in the competition will provide the following benefits to the participants:

• Learn how to build and administrate a cluster system which is an emerging career in Information Technology
• Exposure to new platforms and technologies
• Get a chance to compete in Cluster Building at regional and international level
• Possibility to secure a job with the ZCHPC

Requirements for Students

Students who are interested in the competition must be:

• Studying towards a degree under Science and Technology
• First or Second year student
• In possession of a personal laptop
• Flexible and able to work under pressure

Frankfurt, Germany, June 19, 2017 – Inspur unveiled GX4, a new flexible and high scalability   AI accelerating box at ISC 2017. The GX4 is able to achieve the decoupling coprocessor resources including CPU and GPU, Xeon Phi and FPGA, expand the computing power on demand, and provide highly flexible support to various AI applications in GPU-accelerated computing. This is another innovative effort followed by the release of the ultra-high density AI supercomputer AGX-2 last month at GTC 2017 held in San Jose, California, United States.

Launch view

GX4 makes decoupling and restructuring of the coprocessors and CPU computing resources possible. It enables coprocessors with different architectures, such as GPU, Xeon Phi and FPGA to meet the needs of various AI application scenarios, such as AI cloud, deep-learning model training, and online inference. What’s more important, GX4 expands computational efficiency by connecting standard rack servers with GPU computing expansion modules, overcomes the obstacle that GPU servers need to adjust entire system and motherboard design to change computing  topologies . GX4’s independent computing acceleration module design significantly increases system deployment flexibility, offers high expansion performance from 2 to16 cards, and provides flexible topology changes by changing the connection between server and expansion module, making computing infrastructures and upper-level application better matched, and achieving the best performance of the AI computing clusters.

The New Flexible and High Scalability AI Accelerating Box GX4

The GX4 overcomes the expansion limitation of 8 GPU cards of general AI computing equipment and provides better stand-alone computing performance. Each GX4 supports 4 accelerating cards in 2U form factor, and one head node can connect up to 4 GX4s, achieving 16 accelerating cards in one acceleration computing pool.

Presented by Jay Zhang, VP of Inspur Overseas Headquarter

Jay Zhang, Vice President of Inspur Overseas Headquarter, stated that the GX4 sufficiently addresses the major differences in the AI deep-learning training model, using a flexible expansion method to support different levels of AI training models, and effectively lowering energy consumption and delays. The GX4 provides a flexible and innovative AI computing solution for companies and research organizations engaged in artificial intelligence across the world.

Inspur is dedicated to developing intelligent computing business which focuses on cloud computing, big data and deep leaning, and this has been regarded as the most important business development for the next decade. In recent years, Inspur has become the largest AI computing platform provider in China. Besides, Inspur’s AI solutions’ market share has reached to 60% in China and 80% in China’s BIG 3 IT companies, Baidu, Alibaba and Tencent, and it has been widely- used in smart-voice, smart-image and other applications by companies such as iFlytek and Face++.

https://www.hpcwire.com/2017/06/20/inspur-unveiled-gx4-new-flexible-high-scalability-ai-accelerating-box-isc-2017/

Deep learning is the latest and most compelling technology strategy to take aim at the decades-old “drowning in data/starving for insight” problem. But contrary to the commonly held notion, deep learning is more than a big data problem per se. Delivering on deep learning’s potential – and achieving its anticipated 50 percent annual growth rate market opportunity – involves a highly demanding scaling problem that requires overlapping computational and communications capabilities as complex as any of the classic supercomputing challenges of the past.

That’s the view of Cray senior VP and CTO Steve Scott, who will discuss “pushing the frontiers of deep learning” at ISC in Frankfurt to close out Deep Learning Day (Wednesday, June 21) at the conference.

Scott told EnterpriseTech (HPCwire‘s sister publication) the focus of his session will be on training at-scale neural networks to handle complex deep learning applications: self-driving cars, facial recognition, robots sorting mail, supply-chain optimization and aiding in the search for oil and gas, to name a few.

“The main point I’ll be making is that we see a general convergence of data analytics and classic simulation and modeling HPC problems,” he said. “Deep learning folds into that, and the training problem in particular is a classic HPC problem.”

In short, greater machine intelligence requires larger, more complex models – with billions of model weights and hundreds of layers.

Ideally, Scott said, training neural networks using the stochastic gradient descent algorithm “you’d process one sample of that training data, then update the weights of your model, and then repeat that process with the next piece of training data and then update the weights of your model again.”

Cray’s Steve Scott

The problem, he said, is that it’s an inherently serial model. So even when using a single node, Scott said, users have traditionally broken up their training data into sets – called “mini-batches” – to speed up the process. The entire training process becomes much more difficult when you want to train your network not on one GPU, or 10 GPUs, but on a hundred or thousands of GPUs.

You can simplify training by using lesser amounts of data, but that leads to deep learning systems that haven’t been trained thoroughly enough and, therefore, aren’t intelligent enough. “If you have a small amount of data and you try to use it to train a very large neural network,” Scott said, “you end up with a phenomenon called ‘overfitting,’ where the model works very well for the training data you gave it, but it can’t generalize to new data and new situations.”

So scale is essential, and scale is a big challenge.

“Scaling up this training problem to large numbers of compute nodes brings up this classic problem of convergence of your model vs. the parallel speed you can get,” Scott said. “This is a really tough problem. If you have more compute nodes working in parallel you can process more samples per second. But now you’re doing more work each time, your processing more samples before you can update the model weights. So the problems of converging to the correct model becomes much more difficult.”

Scott will discuss the kind of system architecture required to take on deep learning training at scale, an architecture that – surprise! – Cray has been working on for years.

“It calls for a very strong interconnect [the fabric, or network, connecting the processors within the system], and it also has a lot to do with turning this into an MPI [the communications software used by the programs to communicate via the fabric] problem,” Scott said. “It calls for strong synchronization, it calls for overlapping your communications and your computation.

“We think bringing supercomputing technologies, from both a hardware and a software perspective, to bear can help speed up this deep learning problem that many people don’t think of. They think of it as a big data problem, not as a classic supercomputing problem. We think the core problem here in scaling these larger models is one in which supercomputing technology is uniquely qualified to address.”

Scott said deep learning has taken root to different degrees in different parts of the market. Hyperscalers (Google, Facebook, Microsoft, AWS, etc.) have thousands of projects under development with many, in voice and image recognition in particular, fully operational.

“It’s really past the tipping point,” Scott said. “The big hyperscalers have demonstrated that this stuff works and now they’re applying it all over the place.”

But the enterprise market, lacking the data and the compute resources of hyperscalers, remains for now in the experimentation and “thinking about it” phase, he said. “The enterprise space is quite a bit further behind. But they see the potential to apply it.” Organizations that are early adopters of IoT, with its attendant volumes of machine data, are and will be the early adopters of deep learning at scale.

“We’re seeing it applied to lots of different problems,” said Scott. “Many people, including me, are optimistic that every area of industry and science and beyond is going to have problems that are amenable to deep learning. We think it’s going to be very widespread, and it’s very large organizations with large amounts of data where it will take root first.”

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