Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. These techniques span different types of learning and provide powerful tools to solve complex real-world problems.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

FEBRUARY 22, 2024

months (INR 30,000) Offers self-paced learning and live guidance sessions. This bootcamp includes a dedicated Statistics module covering essential topics like types of variables, measures of central tendency, histograms, hypothesis testing, and more. You will learn by practising Data Scientists.

Hypothesis Testing 52

Hypothesis Testing Data Science Data Analysis Data Analysis 52

Pickl AI

SEPTEMBER 12, 2024

Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities. Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Students should learn about data wrangling and the importance of data quality. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Students should learn how to train and evaluate models using large datasets.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

APRIL 26, 2024

Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Explain the difference between supervised and unsupervised learning. In traditional programming, the programmer explicitly defines the rules and logic.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52