In today’s data-driven world, where AI technologies are becoming increasingly prevalent, Natural Language Processing (NLP) is emerging as one of the most sought-after skills. NLP is utilized in various applications such as web searches, advertisement, customer service, language translation services, sentiment analysis, and more. For individuals looking to establish themselves as leaders in this field, obtaining NLP certifications is crucial. Here, we will explore the top 5 NLP certifications currently available.
1. Natural Language Processing Specialization (Coursera):
This specialization course aims to equip participants with the skills needed to design NLP applications for question-answering and sentiment analysis. The course covers topics such as developing language translation tools, text summarization, and building chatbots. Taught by experts in NLP, machine learning, and deep learning, including Younes Bensouda Mourri from Stanford University and Lukasz Kaiser from Google Brain, the course delves into various aspects such as logistic regression, Naïve Bayes, word vectors, dynamic programming, hidden Markov models, neural networks, LSTMs, GRUs, and more. This intermediate-level course has a duration of 4 months with a commitment of 6 hours per week.
2. Natural Language Processing in TensorFlow (Coursera):
Targeted towards software developers interested in creating AI-powered algorithms, this course focuses on utilizing TensorFlow for building NLP systems. Participants will learn text processing techniques, tokenization, as well as implementing RNNs, GRUs, and LSTMs in TensorFlow. It is recommended to have a basic understanding of Python coding and complete the first two courses of the TensorFlow Specialization before enrolling in this intermediate-level course, which has a duration of 14 hours.
3. Natural Language Processing in Python (Datacamp):
This course provides core NLP skills required for converting data into valuable insights. Participants will learn to transcribe TED talks automatically and work with popular NLP Python libraries such as NLTK, scikit-learn, spaCy, and SpeechRecognition. The course covers building chatbots, transcribing audio files, and extracting insights from real-world sources. With a total of 6 courses and a duration of 25 hours, this course offers a comprehensive overview of NLP in Python.
4. Feature Engineering for NLP in Python (Datacamp):
This course focuses on teaching techniques for extracting useful information from text and processing it for applying ML models. Participants will learn about POS tagging, named entity recognition, readability scores, n-gram and tf-idf models, and how to implement them using scikit-learn and spaCy. The course also covers computing document similarities, predicting sentiment in movie reviews, and building recommenders for movies and TED Talks. With 4 courses, over 50 exercises, and 15 videos, this course provides a solid foundation in feature engineering for NLP.
5. Advanced NLP with SpaCy (Datacamp):
This course introduces participants to spaCy, a popular NLP library in Python, for building advanced natural language understanding systems. The course covers topics such as identifying words, phrases, names, concepts, large-scale data analysis, processing pipelines, and training neural network models. Participants will learn to utilize rule-based and machine learning approaches for NLP tasks.
In conclusion, NLP certifications play a vital role in shaping the future of individuals aspiring to excel in the field of Natural Language Processing. With the top 5 NLP certifications listed above, individuals can enhance their skills, gain practical experience, and stay ahead in this rapidly evolving field. Whether you are a beginner or an experienced professional, these certifications offer valuable insights and hands-on training to propel your career in NLP.