Over the years, the world has become more modern due to adopting the latest and most advanced technologies. Internet of Things(IoT), Big Data, Data Analytics, machine learning, artificial intelligence, and data science are some of the well-known emerging technologies. In this article, we will focus on data science; which enterprises and individuals mainly utilize to increase productivity. Data science is a popular method used to extract useful data from unorganized data. After the important data is extracted, data scientists use it to predict future patterns and behaviors. Note that a data scientist is a person who gathers and analyzes large sets of unstructured and structured data while utilizing his/her skills in mathematics, statistics, and computer science. Hence, with data science, one can collect, analyze and interpret data to prove or disapprove a question or a hypothesis.
Main Applications of Data Science
- Finance: In finance industries, data science applications are used to increase the productivity of a business. From the data science applications, customers’ data is fetched and used to make data-driven decisions as well as design appropriate business strategies. Also, data science analytic tools are applied to predict the future, preventing the finance industries from risk of losses.
- Healthcare: Data science applications have contributed to the improvement in the healthcare sector.It helps in extracting data and making decisions based on health-generated data from modern machines. Also, it is used in virtual medical bots, drug discoveries, detecting tumors, and others.
- E-commerce: With data science, businesses can predict profits and losses. Data science applications help in suggesting new products based on ones frequently bought by the customers. Enterprises make major changes to the products depending on the customers’ reviews or feedback as identified and analyzed by data scientists.
- Gaming: Data science with the help of machine learning utilizes past data to enhance performance and improve the gaming experience for the users. Also, data science has a role in ensuring that the games are designed in a way that the user is fully engaged. Game owners benefit from data science since the applications are made to earn profit for the companies and they are well-created to convince the player to pay for playing.
- Tour and Travels: Travelling is a fun activity since most individuals enjoy exploring the world. Most organizations are using data science to provide better traveling experiences for users. Many industries use data science to offer custom services to people depending on their travel interests or preferences. With the help of data science, users are provided with the travel costs, schedule, and route.
Why Should you Consider Learning Data Science?
Here are some of the reasons to convince to take a course in Data Science:
- Lucrative career: Data science is an excellent career choice where a data scientist earns approximately 163% more than the average national salary. Notably, the data scientist position is prestigious since the organization relies on them to make data-driven decisions. Thus, consider taking a data science course to become a proficient and knowledgeable personnel. Remember that you will gain skills in the field of mathematics, statistics, and computer science.
- High Demand for Data Scientists: Data is being generated in large quantities every day. However, there are no enough data scientists to extract and analyze data to help companies make proper business decisions. Thus, taking a data science course will guarantee you an employment opportunity after you are awarded a certificate.
- Working in various sectors: Data science is applied in different sectors such as health care, digital marketing, finance, and e-commerce. Therefore, studying data science offers you an opportunity to choose the area of business that suits you best.
- Innovation: After gaining skills and experience from a data science course, you are in a good position of making the world a better place. A data scientist can collaborate with different people and come up with projects that will help society at large. Note that you can bring change to the present and future generations if you utilize your knowledge and skills in data science.
Best Video Courses to Learn Data Science in 2022
Let’s dig deep into the video courses you should consider while learning data science in 2022.
1. Data Science A-Z™: Real-Life Data Science Exercises Include
Being passionate about making data science your career calls for finding a course that will boost your skills and experience. Luckily, Data Science A-Z™ by Kirill Eremenko is a video course for either beginners or people who know a little bit more about data science. With the help of this course, you will learn data science through real-life examples and exercises. Get ready for hands-on exercises on topics such as data mining, Tableau Visualization, modeling, or curve fitting of your data. Note that you don’t have to worry about the software to use for practicals since they are either free or available as a demo version. If you dedicate 21 hours to this smooth training, you will earn a data science completion certificate which you can present anywhere.
Once you complete the Data Science A-Z™: Real-Life Data Science Exercises Included course, you will learn how to:
- Clean and prepare data for analysis.
- Perform basic data visualization.
- Curve-fitting data.
- Model your data.
- Present findings.
- Perform Data Mining in Tableau.
- Apply the Chi-Squared statistical test.
- Create and Interpret coefficients of Multiple Linear Regression.
- Interact with tools such as SQL, SSIS, Tableau, and Gretl.
2. The Data Science Course 2022: Complete Data Science Bootcamp
When learning, it is important to know that data science is a multidisciplinary field that encompasses a range of topics. In the Data Science course 2022, you are taught everything that relates to data science such as mathematics, statistics, python, data visualization, tableau, and machine learning. Notably, this complete data science BootCamp guide ensures that the flow of learning these topics is smooth in that after learning the previous section, you can study the next one with zero struggles. In simple words, this data science video course ensures you acquire skills in the right order. Consider starting your data science career with a 30 hours length of video training,90 articles, and 516 downloadable resources. Keep in mind that you will earn a certificate of completion when you finish learning this course.
Some of the sub-topics you will cover in The Data Science Course 2022 include:
- Understanding the data science field.
- Mathematics behind Machine Learning.
- Linear and logistic regressions in Python.
- Creating Machine Learning algorithms in Python.
- How to use Python for statistical analysis.
- Understand the power of deep neural networks.
3. Machine Learning, Data Science, and Deep Learning with Python
To become a data scientist, there is a need to study more about machine learning and how it relates to data science. This particular video course will teach you the techniques required to build real data scientists; who can collaborate with machine learning practitioners and make improvements in the tech industries. Prepare your move into a data science career path by following the 100 lectures and Python code examples provided by this course. Also, you will spend at most 16 hours and access articles that will guide you through the entire course. Note that this is a hands-on machine learning tutorial with data science, artificial intelligence, and neural networks with an addition of a certificate after course completion. An added advantage is the use of plain English, for better understanding and to avoid confusion when studying.
Some of the topics covered in machine learning, data science, and deep learning with Python course include:
- Creating artificial neural networks with Tensorflow and Keras.
- Implementing machine learning at a massive scale with Apache Spark’s MLLib.
- Learn data Visualization in Python.
- Image, data, and sentiments classification with deep learning.
- Classification of data using K-Nearest Neighbor.
- Understanding reinforcement learning.
- Learning Collaborative Filtering.
- Regression analysis.
4. Python for Data Science and Machine Learning Bootcamp
Python is a popular, interpreted, general-purpose programming language. In data science, Python is of great importance since it offers libraries to deal with data science applications. Another significant purpose of Python in data science is it contains tools from mathematical and statistical perspectives. Hence, to become a great data scientist, study this course and gain Python skills that you will later use in the machine learning and data science field. Moireover, you will learn how to use Python when analyzing data, creating visualizations, and applying powerful machine learning algorithms. Bear in mind that this course is for both beginners and experienced developers who want to enhance their skills in data science. You are provided with over 100 HD video lectures, detailed notes and you will spend 24 hours to complete the course and earn a certificate.
Topics covered in the Python for Data Science and Machine Learning Bootcamp course:
- Python for Data Science and Machine Learning.
- NumPy with Python.
- Implementing Machine Learning Algorithms.
- Use pandas for Data Analysis.
- Logistic and Linear Regression.
- Spark for Big Data Analysis
- Using Seaborn for statistical plots.
- K-Means Clustering.
- Random Forest and Decision Trees.
- Natural Language Processing.
5. R Programming A-Z™: R For Data Science With Real Exercises
R programming is an open-source scripting language used for statistical computing. It supports statistical analysis techniques, inference techniques, time series analysis, graphical visualizations, and machine learning models for data analysis. Data science is a popular field that requires important tools to transform raw data into solutions. Thus, R programming is one of the outstanding techniques applied when researching, processing, transforming, and visualizing information. If you feel like R has a steep learning curve, consider taking this course which has simplified R programming to make it more understandable. It is a step-by-step course where every video explains a new concept. Kirill Eremenko has ensured that within 10.5 hours, you can grasp a lot in R programming and earn a certificate. Remember that with or without statistical and programming background, you will learn and finish this course.
Some of the things you will learn include:
- Core principles of programming.
- How to program using R scripting language.
- Using R studio.
- Creating vectors and variables in R.
- Building and using matrices in R.
- Installing packages in R.
- Integer, double, character, logical, and others in R.
6. Complete Machine Learning & Data Science Bootcamp 2022
Machine learning is a core subfield of artificial intelligence defined by the ability of machines to imitate intelligent human behavior. In data science, machine learning offers techniques to extract data and uses well-defined algorithms to predict future trends from the collected data. Hence, this course is frequently updated with data science and machine learning content, and you are allowed to learn everything from scratch. Being a modern and comprehensive course, you are given access to all the code, workbooks, and templates from Github. It has the right resources, 43 hours of on-demand video, 55 reference articles, and a certificate of completion. With the knowledge you will gather from this machine learning and data science course, you will gain the confidence and skills required by employers.
Here are some of the topics you will;l learn from this course:
- How to become a qualified data scientist.
- Machine learning in data science.
- Deep Learning, Transfer Learning, and Neural Networks.
- Learn Data Science and Machine Learning Projects and Workflows.
- Implementing Machine Learning algorithms.
- Programming using the latest Python 3.
- Machine Learning on Time Series data.
- Explore large datasets using data visualization tools.
- NumPy and how it is used in Machine Learning.
- Pandas Data Frames in solving complex tasks.
7. Statistics for Data Science and Business Analysis
Statistics is a popular discipline that focuses on data collection, data analysis, data organization, data visualization, and data interpretation. Therefore, statistics is a set of mathematical tools and techniques that enable us to get answers to crucial questions about data. Lately, statistics has taken a major role in fields such as data science, machine learning, business intelligence, data analysis, and others. It is important to learn statistics since the core concept of data science is built around it.Ace your data science journey by learning the fundamentals of data science and acquiring the skills necessary to solve real-world problems. Notably, this course is well structured to ensure that you understand how statistics is applied in data science and business analysis. In the 5 hours of video training, you will go through outstanding course materials, quizzes, notes, handouts, and high-quality animations. Keep in mind that after the completion of the course, you will receive a certificate.
Some of the topics covered in the Statistics for Data Science and Business Analysis course:
- Fundamentals of statistics.
- Calculate the measures of asymmetry, central tendency, and variability.
- Concepts needed for data science with Python and R.
- Working with different types of data.
- How to calculate correlation and covariance.
- Making data-driven decisions.
- Caring out regression analysis.
- Performing hypothesis testing.
8. Intro to Data Science: Your Step-by-Step Guide To Starting
If you are new in the field of data science, this is the right course for you. It is a beginner course that will help you understand data science at a deeper level. Also, you will learn how data science concepts are applied together with the most used tools and techniques. Note that the video training is 5 hours long with 42 lectures that explain data science through seven split sections. As a passionate data scientist, this course will give you the skills leading you towards your desired destinations. Some of the tools you will interact with in this course include SQL, tableau, and Python, and get assistance in launching your data science projects. After acquiring data science expertise from this particular course, you are awarded a certificate of completion.
Topics covered in this course include:
- Entire Data Science process.
- Statistics fundamentals for Data Science.
- Cloud concepts in Data Science.
- Machine Learning.
- Advanced Python and application in Data Science.
- Visualizations for data mining and presentation.
9. Data Science: Deep Learning and Neural Networks in Python
In your data science learning journey, you will interact with neural networks and deep learning. In this course, you are taught how to build your first artificial neural network with the use of deep learning techniques. Note that neural networks reflect the behavior of a human being’s brain, enabling a computer program to recognize patterns and solve problems in machine learning, artificial intelligence, data science, and deep learning. Also, neural networks help data scientists when solving business problems that include copious amounts of data. Therefore, this is an important course to take and become a data science professional after following 11 hours of on-demand video. You will be given projects to assist you in understanding deep learning and how you can use it to predict users’ actions. By the end of this course, you will learn a lot and earn a certificate of completion.
Some of the topics in the Data Science: Deep Learning and Neural Networks in Python course are:
- Understanding Deep Learning.
- How a neural network is built from basic building blocks.
- Installing TensorFlow.
- Coding a neural network with Google’s TensorFlow.
- Coding a neural network from scratch in Python and NumPy.
- Derive the backpropagation rule from first principles
10. Careers in Data Science A-Z™
Data science is an excellent career choice that you should consider in this modern era. Due to the high demand for data scientists, there is a shortage of qualified or skilled professionals. Thus, if you have made up your mind to start your journey in data science, this is the perfect course for you. Data Science A-Z™ is a course that will deliver valuable lessons, advice, tips, and insights that will boost your confidence in your data science career. Also, it includes the experiences and lessons from experts in data science who have been in the field for many years. To earn a certificate of completion, you will dedicate 3.5 hours to the careers in data science video course. Enroll in this course and get to know what it takes to become a top data scientist, the salary, promotions, and how to pass and handle interviews.
Here are some of the topics you will go through in this course:
- How to become a Data Scientist.
- Taking data science career to a higher level.
- Tips and tricks in data science.
Final Thought
A data scientist is an important person in our society. If you are a data science enthusiast, it is necessary to take several courses to streamline your career. Thus, this article has listed and explained the best video courses to learn data science in 2022. These top-notch courses will equip you with the skills and expertise required in the field of data science. Make a difference in this digital world by joining the field of data science; with the help of the knowledge, you will attain from the above courses.
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