Trading to Financial Modeling Pro: Ramit's PGFAP Story | Postgraduate Financial Analysis Program

Accounting and finance have seen a radical shift in recent years, more women are joining and succeeding in what used to be men's turf. A clear proof of the new trend is the increasing number of women becoming members of ACCA (Association of Chartered Certified Accountants) . With global recognition and a broad syllabus, ACCA has become a promising platform for women to rise to the ranks of executives in finance, auditing, taxation, and consultancy. The Rise of Women in ACCA Over the past few years, a trend has been observed worldwide wherein half of the students who enrolenroll for the ACCA are females. This is a clear indication of the growing ambition amongst ladies in the financial sector. When compared to the other financial and accounting qualifications, ACCA has a much more flexible approach, making it appealing for women, managing studies, work, and home.  ACCA promotes diversity and inclusion. Mentorship, networking, and leadership development facilities are beneficial to w...

  Principal Component Analysis (PCA) is one of the most useful techniques in the field of data science and machine learning. It helps reduce the number of variables in a dataset while keeping the key information. If you're just starting your journey in data, PCA is something you’ll likely come across—and understanding it is easier than you might think. At Imarticus Learning , we break down PCA in a way that’s simple, clear, and easy to follow. What is PCA and Why Does It Matter? PCA is short for Principal Component Analysis. It’s a method used to simplify large, complex datasets. Let’s say your dataset has many columns (also called features). PCA helps reduce these columns into a smaller number without losing the important data patterns. This process is known as dimensionality reduction . Why do we reduce dimensions? Because smaller, cleaner datasets often lead to faster training times and more accurate machine learning models. PCA also helps with better data visualization, mak...

If you're aiming for a career in finance or banking, taking admission to a PG banking and finance course is among the most sensible decisions you could take. Designed to equip first-time graduates and young professionals with hot skills, sector-specific experience, and in-depth knowledge in the BFSI domain, such courses are must-haves these days. Be it theoretical know-how or field experience and internships, read on for an entire overview of what you could gain through this course. Finance Curriculum Overview: What You’ll Learn A good PG banking and finance course includes a well-structured finance curriculum overview designed to give students a deep understanding of the banking and financial ecosystem. Here’s a quick explanation before diving into the modules. The curriculum is broken into core finance concepts, practical banking systems, compliance regulations, & digital banking tools. These topics are updated regularly to meet the industry’s current demands. Key modules in...

 Careers in the data science space are among the most lucrative in the tech industry. From predictive analytics to AI and automation, the demand for data professionals is booming. With industries embracing artificial intelligence (AI) and machine learning (ML) , jobseekers are eyeing high-paying tech careers across domains. Here’s a guide to the best-paying roles, their salaries, and growth potential. Why Data Science Is a High-Paying Field Data is the new currency. Businesses need experts to collect, analyse, and extract insights from massive datasets—insights that drive automation, forecasting, and strategic decisions. Why data science pays well: Huge demand and limited supply of talent Specialised skills in AI and ML command premium salaries Strong need for analytical thinking and programming expertise Top AI Job Roles in 2025 AI is at the core of modern digital transformation, and its intersection with data science opens doors to high-paying, globally in-dem...

Time Series Modelling plays a critical role in shaping decisions across industries—from predicting stock prices in finance to forecasting product demand in retail and optimizing resources in healthcare. For anyone venturing into data science, understanding time series data is not just valuable—it's essential. This article breaks down the basics of time series analysis, introduces key algorithms like ARIMA, SARIMA, and Prophet, and explains why mastering these concepts can pave your path to a successful career with the best data science and analytics course. Watch the full video now to understand how businesses forecast sales, demand, and stock prices using real-world time series models like ARIMA and Prophet. Start your journey with industry-relevant insights.  What Is Time Series Data? Time series data consists of observations collected at specific time intervals—be it hourly, daily, weekly, or monthly. What sets this data apart is its sequential nature and time-based patterns. Un...