In an era where data is everywhere – those who know how to interpret it correctly possess a critical ability to lead processes and successes.
Our course was created for exactly this: to take you from raw numbers to smart business insights. Without focusing on technical tools, but on learning the thinking behind the data.
Real-world case studies – declining product performance, improving marketing strategies, fraud detection, audience analysis, and more
You will work on the assignments under the close supervision of a supervisor, who will guide, check, and provide personal feedback that will advance you to true professionalism.
It's not enough to analyze – you also need to explain, convince, and recommend. Learn how to translate data into concrete conclusions.
At the end of the course, you will leave with a set of professional analyses ready to present. This is a real competitive advantage for those aiming for roles in the data world.
Whether you are already in the position or in the process of entering the position, the knowledge you acquire will affect how you think and present results.
Thinking structure, problem-solving templates, tools for presenting insights – the course provides methodologies that can be applied again and again.
The team that leads our courses doesn’t just come from the classroom – they also come from the field. They live the world of data every day, teach from real experience, and know how to explain the most complex things in the most clear way. In short – you’re in good hands.
Ram Kedem – has lived in the world of Data for over 15 years, led diverse projects, professionally managed leading colleges, mentored tens of thousands of people, and wrote literature in the field of Data that is sold worldwide.
Gadi Chrust is the head of the analysis team at Plarium. Plarium is one of the largest social gaming companies in the world with over 400 million users. Gadi has many years of technical and business experience, and as part of his work he has interviewed dozens of analysts.
Michael Winner – Principal Data Scientist at the startup Yess. In addition, he worked and led data science initiatives and teams at AppsFlyer and Digital Turbine. Over 7 years of experience as a data scientist and team manager in the field, and 10 years of experience in the data field.
Dotan Antin is an analyst and BI developer at Applied Materials, a company that develops and manufactures systems that form the infrastructure of the global chip industry.
Dotan brings with him extensive experience and knowledge, and as part of his work he deals with various BI technologies.
Aviv Gelfand is a data scientist at the tech company Darrow AI. He holds a BA in statistics and data science from the Hebrew University. He is writing a thesis in the field of language models and methods to save runtime and memory in them, as part of his master’s degree at the Hebrew University.
Omar Bieber is the Head of BI at Superplay, one of the fastest growing gaming startups in the world. Omar brings with him extensive experience in the BI world from companies like Playtika and HiBob.
This is what it sounds like when learning really makes a difference.
An inspiring journey that significantly boosted my analytical skills and elevated my professionalism to an entirely new level.
Thank you for your exceptional ability to break down complex statistical concepts into manageable pieces
if you are looking to expand your data analysis capabilities and explore real-world applications, I strongly recommend considering Upscale Analytics.
A challenging yet eye-opening course - perfect for those with strong analytical skills aiming to advance into machine learning.
A truly transformative course that bridges the gap between data analysis and machine learning with Python — practical, innovative, and expertly delivered.
Highly recommended for anyone looking to level up their skills — top-notch teaching based on the most relevant, up-to-date material.
Big thanks to the amazing Upscale Analytics team – the best professionals to learn from, with outstanding content and teaching!
Remarkable experience that strengthened my data analysis skills and critical thinking — thanks to Upscale's expert, supportive, and inspiring team.
I'm immensely grateful to the teaching staff for their unwavering support and guidance throughout this journey, as it has led to a rapid and fulfilling transformation in my data analysis skills.
Grateful to the amazing teaching staff for their support and guidance throughout this rewarding journey that truly elevated my analytical skills.
A hands-on journey that deepened my understanding of data and sharpened my ability to extract insights — huge thanks to the Upscale team!
This course gave a major boost to my skills as a Data Analyst — covering Linear Regression, XGBoost, K-means, Ensembles, and more.
Awesome course! Learning from amazing instructors alongside a talented group made it truly special. Highly recommended for anyone looking to grow in data.
Huge appreciation to the Upscale Analytics team for their mentorship and dedication. Professional, attentive, engaging - with real-world examples that bring every concept to life.
During this session we’ll understand the main stages in the Data Analysis process, and present a Use-Case that demonstrates an analysis of a real data-set from end to end.
Identify reasons behind a decline in a top game's performance, focusing on daily active users, revenue, and user spending segmented by Lifetime Value and platform.
Analyze a dataset of marketing bids to identify trends in win rates and conversion rates, and suggest improvements. Data includes user details, device info, auction types, and outcomes. This analysis focuses on understanding and enhancing marketing strategy effectiveness.
Conduct a descriptive analysis on treadmill purchase data to profile customers for each product type. Examine variables like age, gender, education, marital status, usage, fitness level, income, and expected mileage to understand preferences and sales trends. Utilize insights to recommend specific treadmills to potential customers and strategies to boost sales.
Analyze a dataset of orders to establish rules or thresholds for automatically accepting or denying new orders based on fraud risk. The data includes order value, email score, billing and shipping country codes, IP country, and proxy scores.
Analyze data from an A/B test. The test aims to assess the feature's impact on revenues, and number of paying customers. Draw conclusions and provide recommendations based on observed trends and results.
Analyze data from an A/B test. The test aims to assess the feature's impact on revenues, and number of paying customers. Draw conclusions and provide recommendations based on observed trends and results.
Analyze two weeks of data from a city's ride-hailing service to optimize operations and identify areas for improvement. Assess key metrics such as the date with the most completed trips, busiest hours, driver-to-trip ratios, and demand-supply dynamics.
Analyze an extensive dataset to provide strategic insights on content preferences across different countries and trends over time. Focus on content types available globally, changes in movie releases over decades, optimal launch timing for TV shows, and the role of actors and directors in different genres.
During the training, each student will receive access to the learning management system, which is designed to enrich the learning experience and assist in achieving course objectives.
The system offers a wide range of tools and resources that enable effective and convenient learning:
To be eligible for a course completion certificate, the following requirements must be met:
Is the course also suitable for those who do not yet work in the data field?
Yes. The course is structured to be suitable for those who are just starting out, including those preparing for analytical interviews or people who want to develop the ability to understand and work with data intelligently.
What level of technical knowledge is required?
The course does not require experience in programming or statistics. It does require basic familiarity with Excel, such as using simple functions, arranging tables, and creating graphs. Those who need reinforcement will receive a prepared playlist in advance.
Are there practical exercises during the course?
Absolutely. Each class includes practical data analysis practice on a real scenario, including homework, guided work, and personal guidance in generating insights.
What happens if I miss a class?
All sessions are recorded and can be accessed at any stage during the course and up to 4 months after completion.
What does the support and guidance look like during the course?
You will receive personal guidance from the instructor throughout the entire process – including feedback on exercises, answering questions between lessons, and professional guidance in dealing with challenges.
What is the cancellation policy?
Satisfaction guaranteed – if after the first two sessions you feel the course is not right for you, you will receive a full refund. No fine print.
Does the course include a certificate of completion?
Yes. A certificate will be given to participants who met the course requirements and attended at least 80% of the sessions.
