Welcome! I have listed down a variety of courses designed to help professionals enhance their skills in the field of data analytics. With over 20 years of experience in data, analytics, and technology, I am dedicated to providing comprehensive and engaging training programs that cater to professionals of all levels of expertise.
My courses cover a wide range of topics, including Data-driven decision making / Decision science, Business statistics, Python programming, Data science / Machine Learning, and First principles thinking. These courses are designed to help you acquire the necessary skills and knowledge to excel in today’s data-driven world, and make informed decisions that drive business growth and success.
By taking there courses, you will have the expertise and know-how to guide you through the ins and outs of data analytics. Whether you are a beginner or an experienced professional, our courses will help you stay ahead of the curve and take your career to the next level. So why wait? Drop me a message and we can work together to get you started on your journey towards becoming an expert in the field of data analytics. My email address is ajitesh@gmail.com. You can also connect me on Linkedin and start the discussion(linkedin.com/in/ajitesh )
Data-driven decision making is a crucial aspect of modern business operations. Making informed decisions based on data insights can help organizations achieve their goals more effectively, and ensure that they remain competitive in their respective industries. The course on data-driven decision making covers a wide range of topics that are essential for professionals looking to hone their skills in this field. The following are some of the key topics covered as part of this course:
The data-driven decision-making course is perfect for those looking to hone their decision-making skills and take their knowledge to the next level. My comprehensive training program covers everything from the basics of business statistics and decision science, to the most advanced methods of data science and machine learning. You’ll learn essential skills like how to analyze data, build models, and make better decisions.
The business statistics course teaches you the fundamentals and fundamentals of data analysis and statistics. You’ll learn how to use statistical software like Python, R and Excel, and you’ll also get hands-on experience with real-world data sets. Our practical approach to teaching will enable you to apply your newfound knowledge to your everyday work.
The course on Business Statistics is designed to provide participants with a strong foundation in statistical concepts and their practical applications in business decision making. Here are the key course modules that we cover:
If you’re looking to level up your programming skills, the Python programming course is the perfect choice. I’ll teach you the basics of Python programming and help you understand how to write code efficiently. You’ll also learn how to use popular libraries, such as pandas and scikit-learn, and how to process data with Python. By the end of the course, you’ll be able to write efficient code and apply it to real-world problems.
Here is the high-level information about the training course in python programming including key topics that will be taught:
Introduction to Python: This topic would cover the basics of Python programming language, such as variables, data types, operators, and control structures. It would also provide an overview of the Python environment, including installation and configuration.
Functions and Modules: This topic would cover how to write and use functions in Python, as well as how to import and use modules. It would also introduce the concept of libraries and packages in Python.
Data Structures: This topic would cover the various data structures in Python, such as lists, tuples, sets, and dictionaries. It would also cover how to manipulate and access these data structures.
Object-Oriented Programming: This topic would cover the principles of object-oriented programming in Python, including classes, objects, inheritance, and polymorphism. It would also cover how to create and use objects in Python.
File Handling: This topic would cover how to read and write files in Python, including text files and CSV files. It would also cover how to handle errors and exceptions when working with files.
Web Scraping: This topic would cover how to extract data from websites using Python. It would cover libraries such as Beautiful Soup and Requests, as well as how to parse HTML and XML.
Data Analysis: This topic would cover how to perform data analysis in Python using libraries such as Pandas and NumPy. It would cover how to manipulate and analyze data, as well as how to visualize data using libraries such as Matplotlib.
Django Web Development: This topic would cover how to develop web applications using the Django web framework in Python. It would cover how to create views, templates, and models, as well as how to handle forms and authentication.
Take your data analysis skills to the next level with my course on machine learning. The course covers the fundamentals of machine learning, from exploring and analyzing data to creating data-driven models and machine learning algorithms. I will guide you through the process of understanding and using data to make better decisions and improve your skills as a data scientist.
Here is the high-level information about the training course in machine learning including key topics that will be taught:
Introduction to Machine Learning: This topic would cover the basics of machine learning, including the different types of machine learning, the machine learning workflow, and the key concepts and terminology used in machine learning.
Supervised Learning: This topic would cover the supervised learning approach, which involves training a model on labeled data to make predictions on new, unseen data. It would cover techniques such as regression and classification, as well as algorithms such as linear regression, logistic regression, decision trees, and random forests.
Unsupervised Learning: This topic would cover the unsupervised learning approach, which involves training a model on unlabeled data to identify patterns and relationships in the data. It would cover techniques such as clustering and dimensionality reduction, as well as algorithms such as K-means clustering, hierarchical clustering, and principal component analysis.
Deep Learning: This topic would cover deep learning, which is a subset of machine learning that involves training models on large amounts of data using neural networks. It would cover techniques such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), as well as applications such as image recognition and natural language processing.
Model Evaluation and Validation: This topic would cover how to evaluate and validate machine learning models, including techniques such as cross-validation, precision and recall, and the ROC curve. It would also cover how to avoid overfitting and underfitting in machine learning models.
Feature Engineering: This topic would cover how to preprocess and transform data to improve the performance of machine learning models. It would cover techniques such as scaling and normalization, handling missing values, and feature selection.
Model Deployment: This topic would cover how to deploy machine learning models in real-world applications, including techniques such as model optimization and serving, and the use of application programming interfaces (APIs).
Each of these key topics is important for beginners to learn in Machine Learning as they cover the foundational concepts and skills needed to become proficient in Machine Learning. By learning these topics, beginners would be able to apply Machine Learning to various problems, from basic regression and classification tasks to complex image recognition and natural language processing problems.
Business analytics training is the perfect way to gain an understanding of the fundamentals of business analytics. My comprehensive course will equip you with the knowledge and skills to arrive at the most appropriate use cases, value metrics, analyze data, track performance, and gain valuable insights into the business. With this training, you will acquire the foundation and knowledge needed to realize value while leveraging data analytics.
The training program is designed to help individuals master the practice of first principles thinking. Through the comprehensive training, you will gain the skills and knowledge to think more deeply and critically, unlocking your potential. The program is designed to provide you with the tools and guidance needed to understand and apply first principles thinking.
If you are interested in any of the above courses, please drop me a message at ajitesh@gmail.com