Curated learning path for AI Metering & Usage Analytics. Build practical skills through expert-selected courses.
Basic statistics helpful; will be taught
Some coding experience; Python or R preferred
Fraud Analytics With AI/ML
IntermediateMSc Fashion Analytics and Forecasting
IntermediateCompetitive Intelligence and Analytics
IntermediateAI-Driven Cost and Price Analysis
IntermediateIntrodução a Machine Learning, Data Analytics e Data Science
IntermediateData Analytics, Data Science, & Machine Learning - All in 1
BeginnerData science, machine learning, and analytics without coding
IntermediateDATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS
AdvancedFraud Analytics With AI/ML
IntermediateMSc Fashion Analytics and Forecasting
IntermediateCompetitive Intelligence and Analytics
IntermediateAI-Driven Cost and Price Analysis
IntermediateIntrodução a Machine Learning, Data Analytics e Data Science
IntermediateData Analytics, Data Science, & Machine Learning - All in 1
BeginnerData science, machine learning, and analytics without coding
IntermediateDATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS
AdvancedFollow these courses in order to complete the learning path. Click on any course to enroll.
A course aimed at providing the necessary tools and techniques to succeed in the changing field of financial fraud prevention. It features insights from an instructor with over 25 years of experience in Fraud Detection and AI/ML.
This Master's program is one of the first in the world to apply data analytics and forecasting in the context of fashion business. It combines creativity with analytics, teaching students how to use data-driven technologies to make informed decisions, model demand, and revolutionize traditional business models in the fashion industry. The course is delivered online and is supported by Stylumia, a global trend forecasting company.
This certificate program equips professionals with the skills to turn data into actionable insights for strategic decision-making in global markets. It emphasizes ethical practices and the use of cutting-edge tools, including generative AI. The curriculum covers mastering the CI cycle, applying analytical frameworks, and leveraging AI tools for data collection and visualization to design actionable intelligence reports.
A training program designed to equip professionals with the skills to leverage artificial intelligence for optimizing cost and price analysis. The course explores cutting-edge AI techniques and tools to enhance decision-making and profitability.
Machine Learning é uma disciplina da área da Inteligência Artificial que, por meio de algoritmos, dá aos computadores a capacidade de identificar padrões em dados massivos e fazer previsões (análise preditiva).Data Science é o estudo disciplinado dos dados e informações inerentes ao negócio e todas as visões que podem cercar um determinado assunto. É uma ciência que estuda as informações, seu processo de captura, transformação, geração e, posteriormente, análise de dados para converter em evidência.A Análise de Dados é um processo de inspeção, limpeza, transformação e modelagem de dados com o objetivo de descobrir informações úteis, informar conclusões e apoiar a tomada de decisões. A análise de dados tem múltiplas facetas e abordagens, abrangendo diversas técnicas sob uma variedade de nomes, e é usada em diferentes domínios dos negócios, ciências e ciências sociais. No mundo dos negócios de hoje, a análise de dados desempenha um papel tornando a tomada de decisões mais científicas e ajudando as empresas a operar com mais eficácia Neste curso você vai entender que juntos a Data Science, Machine Learning e Data Analytics além de inovações tecnológicas são aliados para o bom funcionamento das ações organizacionais, e tem poder de influência em toda cadeia produtiva.Bons estudos!
Embark on a transformative journey into the world of Data Analytics, Data Science, and Machine Learning, where you’ll learn the essential skills, tools, and mindsets to become a successful data professional. This comprehensive program is designed to take you from beginner to advanced, equipping you with the knowledge and practical experience needed to excel in the field.Whether you’re looking to kickstart a career in data analytics or enhance your existing skills, this course will empower you to succeed in the dynamic world of data. Join us on this exciting path and unlock your potential in just 60–100 days of disciplined learning.Why This Course Matters Most learners struggle with fragmented resources, inconsistent guidance, or theory-heavy content that doesn’t build real competence. This course solves that problem. It’s structured to provide step-by-step, cumulative, and daily progress — helping you turn knowledge into capability, and capability into career readiness.We are in the AI revolution, and every industry is transforming with tools like ChatGPT, Stable Diffusion, and AI copilots for writing, coding, design, analytics, and more. This course ensures you don’t just learn theory — you’ll build real-world solutions that make you job-ready.1. Foundations of Data Analytics, Data Science & Python Learn how to think like a data scientist, not just how to write code.Python fundamentals: variables, loops, conditionals, functions, data structures.Clean, modular, reusable coding practices for data workflows.Importing and handling real-world datasets with Pandas and Num Py.Data types, memory optimization, and performance tuning.A-Z data cleaning and manipulation techniques: sorting, filtering, pivot tables, and charts.2. Excel, SQL, Python & Power BI Profi
Do you want to super charge your career by learning the most in demand skills? Are you interested in data science but intimidated from learning by the need to learn a programming language?I can teach you how to solve real data science business problems that clients have paid hundreds of thousands of dollars to solve. I'm not going to turn you into a data scientist; no 2 hour, or even 40 hour online course is able to do that. But this course can teach you skills that you can use to add value and solve business problems from day 1.This course is different than most for several reasons:1. We start with problem solving instead of coding. I feel like starting to code before solving problems is misguided; many students are turned off by hours of work to try to write a couple of meaningless lines rather than solving real problems. The key value add data scientists make is solving problems, not writing something in a language a computer understands.2. The examples are based on real client work. This is not like other classes that use Kaggle data sets for who survived the Titanic, or guessing what type of flower it is based on petal measurements. Those are interesting, but not useful for people wanting to sell more products, or optimize the performance of their teams. These examples are based on real client problems that companies spent big money to hire consultants (me) to solve.3. Visual workflows. KNIME uses a visual workflow similar to what you'll see in Alteryx or Azure Machine Learning Studio and I genuinely think it is the future of data science. It is a better way of visualizing the problem as your are exploring data, cleaning data, and ultimately modeling. It is also something that makes your process far easier to explain to non-data scientists making it easier to work with other parts of your business.Summary: This course covers the full gamut of the machine learning workflow, from data and business u
DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R Programming, PYTHON Programming, WEKA Tool Kit and SQL. This course is designed for any graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using R programming, Python Programming, WEKA tool kit and SQL.Data is the new Oil. This statement shows how every modern IT system is driven by capturing, storing and analysing data for various needs. Be it about making decision for business, forecasting weather, studying protein structures in biology or designing a marketing campaign. All of these scenarios involve a multidisciplinary approach of using mathematical models, statistics, graphs, databases and of course the business or scientific logic behind the data analysis. So we need a programming language which can cater to all these diverse needs of data science. R and Python shines bright as one such language as it has numerous libraries and built in features which makes it easy to tackle the needs of Data science.In this course we will cover these the various techniques used in data science using the R programming, Python Programming, WEKA tool kit and SQL.The most comprehensive Data Science course in the market, covering the complete Data Science life cycle concepts from Data Collection, Data Extraction, Data Cleansing, Data Exploration, Data Transformation, Feature Engineering, Data Integration, Data Mining, building Prediction models, Data Visualization and deploying the solution to the customer. Skills and tools ranging from Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, programming languages like R programming, Python are covered extensively as part of this Data Science training.
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