Refonte Learning was established with the vision of bridging gaps between education and industry, providing students with the knowledge and practical skills necessary to thrive in a digital world. With operations across the United States, Canada, the United Kingdom, the EU, the UAE, Russia, India, and Australia, Refonte Learning’s training programs provide participants with practical exposure, helping them to build industry-specific skills and practical work experience, positioning them for a triumphant career debut.
The role of data analyst involves collecting, cleaning, and interpreting data to answer specific questions or problems. Data analysts work in many industries, including business, finance, science, medicine, criminal justice, and government.
Questions data analysts might be tasked with answering include:
- Which demographic should a business target in its next ad campaign?
- What behavioral patterns are associated with financial fraud?
- Which age group is most vulnerable to a particular disease?
Data analysis can take various forms, including diagnostic, descriptive, and predictive. The field is critical to the corporate world, unlocking hidden patterns and insights from information and empowering businesses to make data-driven decisions, enabling them to optimize operations and gain a competitive edge.
Today, data analytics drives innovation, paving the way for smarter decision-making across industries, having emerged as a cornerstone of modern business strategy. As organizations become increasingly data-driven, demand for skilled data analysts continues to increase, presenting lucrative opportunities for those interested in entering or advancing in this dynamic field.
For data analysts and related professionals, the future looks bright, with increasing investment in data-driven innovation, AI, and advanced analytics. Salaries across roles like data engineer, NLP engineer, and data scientist are predicted to rise sharply throughout 2025, with experts forecasting substantial financial growth.
2025 projections for data professionals suggest that entry-level data analysts could expect to earn up to $95,000, rising to $155,000 for those working at a senior level. Mid-level data engineers can expect to earn between $120,000 and $145,000, while data architects could command a paycheck of anywhere up to $210,000.
Refonte Learning’s data analytics program helps beginners to develop a systemic approach, providing vital skills for a successful career in data analytics. Serving as a guiding partner to those who are unsure where to start in their journey into the world of data analytics, Refonte Learning presents opportunities to work on concrete projects, collaborating with professionals, gaining real-world experience, and developing in-depth skills. Refonte Learning’s data analytics program provides the knowledge and skills necessary to excel, covering essential concepts such as the foundations of data exploration, mapping techniques and capabilities in Tableau, and advanced Excel functionalities.
Refonte Learning’s courses go far beyond theory, with the leading learning institution’s immersive virtual internship program presenting opportunities to gain valuable hands-on experience tackling real-world challenges. Data analytics can seem like a daunting and overwhelming field for the uninitiated, but Refonte Leaning’s expert tutors provide seasoned guidance, igniting each student’s journey and setting them on the path to becoming a future-ready professional.
Spanning three months in total, Refonte Learning’s data analytics program is a 12- to 14-hour-per-week course that positions candidates for a range of different roles, including data analyst, data scientist, and machine learning engineer. Students will develop a range of different competencies, including:
- EDA and data visualization
- Python for business analytics
- SQL database
- Deep learning methods and techniques
- Machine learning and predictive modeling
- Model optimization and problem-solving techniques
Refonte Learning’s Department of Data Analytics is led by Helena Ferreira PhD, a professor and mentor with more than 13 years of experience in computer science. A passionate trainer and educator, Professor Ferreira has developed algorithms for cab retention, conducted research on advanced regression, explored big data analytics in banking and financial services, and delved into financial econometrics and quantitative risk forecasting.