Top Data Science Crash Courses to Shape Your Career in 2021 – Analytics Insight

Data Science Crash Courses

These data science crash courses can benefit data enthusiasts to great extents

As the demand for data science professionals grows rapidly, students are looking for data science crash courses to gain the necessary knowledge and high-end skills needed to tackle real-world challenges. Here are the top data science courses for data aspirants to pursue.

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MicroMasters Program in Statistics and Data Science-edX

Level: Intermediate

Duration: 14months (10-14 hours weekly)

The program features a five-course series formulated to boost the foundation of data scientists in the areas of machine learning, data science, and statistics. This course is best suited for students wanting to learn big data analysis. The course gives you a deep understanding of statistics, data analysis techniques, machine learning algorithms, and probability. After the course, the students can apply for roles such as system analyst, data analyst, data scientist, etc. This is one of the data science crash courses that is best suited for students.

Data Science Specialization Course- Coursera

Level: Beginner

Duration: 11months (7 hours weekly)

The data science specialization course includes all the tools and concepts that are needed in your data science journey. These data science courses can help you learn skills to deal with real-world data-related problems. Students will be able to learn about Github, R programming, machine learning, data science, regression analysis, debugging, data analysis, data manipulation, data cleaning. This is one of the data science crash courses that is best suited for students. It includes two components, including the know-how of how to turn data into actionable knowledge.

Machine Learning, Data Science, and Deep Learning with Python-Udemy

Level: Intermediate

Duration: 14hours (approximately)

The course covers all the major topics related to machine learning, including artificial neural networks, and K-means clustering. These data science courses cover neural networks and deep learning, sentiment analysis, regression analysis, multiple regression, collaborative filtering, reinforcement learning, feature engineering, hyperparameter tuning, and many more. This is one of the data science crash courses that is best suited for students. You can opt for this specialization even if you are new to Python as it features a crash course for better understanding.

Machine Learning with Javascript

Level: Intermediate

Duration: 17.5 hours (approximately)

The course is designed for Javascript developers, this machine learning course will take you into the depths of advanced memory profiling, writing ML code, and building Tensorflow JS library-powered apps. This is one of the data science courses that teaches the tricks and techniques of speeding up matrix-based codes with linear algebra basics. This is one of the data science crash courses that is best suited for students. The interesting part is that you can go for this course even if you don’t have any mathematics background as the lectures don’t involve challenging math concepts.

The Complete Machine Learning Course with Python-Udemy

Level: Beginner-Intermediate

Duration: 17.5 hours (approximately)

The course helps in building a strong foundation in Machine Learning. These types of data science crash courses will help you understand the difference between machine learning and classical programming, machine learning, and deep learning. Students will be able to learn about linear regression with scikit-learn, robust regression, cross-validation, logistic regression, radial basis function, linear SVM classification, kNN introduction, and clustering.

Data Science: Machine Learning-Harvard University

Level: Beginner

Duration: 8weeks (2-4hours per week)

This course is offered by Harvard University that helps data science students to help learn machine learning and all the technical problems associated with it. It also gives deep insights into ML’s data science methodologies. The main features of these data science crash courses include ML algorithms, building recommendation systems, cross-validation, and many more.

Intro to Machine Learning with PyTorch-Udemy

Level: Intermediate

Duration: 3 months (10hours per week)

This is a Nanodegree program that is ideal to enhance the skills and knowledge in supervised models, machine learning algorithms, and data cleaning. These data science courses are divided into different steps, with each one offering practical experience to the learners where they can test their skills using code projects and exercises. This is one of the data science crash courses that is best suited for students. The main features of the course are model construction, neural network design, Pytorch training, unsupervised learning method implementation, and deep learning.

HarvardX’s Data Science Professional Certificate

Level: Beginner

Duration: 1year five months (3hours/ week)

The program helps students to learn all the data analysis-related solutions. The features of these data science crash courses include data science basics, visualization, and probability, inference and modeling, productivity tools, wrangling, linear regression, capstone. This is one of the data science courses for students to upskill themselves.

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