Overview
“ Our upskilling programs focuses on gaining hands-on Emerging Tech skills in Data Science (Data Analysis, Data Visualization, Machine Learning, Deep Learning, Artificial Intelligence) which is sought after by Employers in Digital Technology sectors, CleanTech, Advanced Manufacturing, Business Intelligence, Finance and Healthcare sectors. ”
Curriculum
Programming Languages and Tools
Participants will develop proficiency in programming languages commonly used in Data Science such as Python. They will also gain experience in utilizing popular Data Science libraries and frameworks including NumPy, Pandas, Bokeh, scikit-learn, TensorFlow and Keras.
Data Analysis and Manipulation
Participants will gain proficiency in working with large datasets, cleaning and preprocessing data, handling missing values and transforming data into suitable formats for analysis.
Machine Learning Algorithms
Participants will learn various Machine Learning algorithms, including both supervised and unsupervised techniques. They will understand the concepts behind algorithms such as linear regression, logistic regression, decision trees, random forests and clustering algorithms.
Deep Learning and Neural Networks
Participants will delve into the field of deep learning, specifically focusing on neural networks. They will learn about different types of neural networks, such as feedforward neural networks, convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Participants will also gain hands-on experience in building and training neural network models.
Predictive Modeling
Participants will acquire skills in developing predictive models using statistical techniques and Machine Learning algorithms. They will learn about model evaluation, feature selection, model optimization and handling overfitting and underfitting issues.
Data Visualization
Participants will learn how to effectively visualize and communicate data insights using various data visualization libraries and tools. They will gain proficiency in creating visually appealing and informative charts, graphs and dashboards to convey data-driven narratives.
Experimental Design and Evaluation
Participants will learn how to design experiments and perform rigorous evaluation of Data Science models. They will gain an understanding of cross-validation, model validation techniques and metrics for model evaluation.
Data Ethics and Privacy
Participants will be educated on ethical considerations in Data Science, including privacy concerns, data security and responsible data handling practices. They will learn about regulations and best practices to ensure compliance and ethical decision-making in their work.
These technical skills are aligned with based on our employer consultations and the current market demand in the Data Science field. By mastering these skills, participants will be well-equipped to tackle real-world data challenges and contribute effectively to the industry.
These technical skills are aligned with based on our employer consultations and the current market demand in the Data Science field. By mastering these skills, participants will be well-equipped to tackle real-world data challenges and contribute effectively to the industry.
